CN115866634A

CN115866634A - Network performance abnormity analysis method and device and readable storage medium

Info

Publication number: CN115866634A
Application number: CN202111119415.7A
Authority: CN
Inventors: 许瑞岳; 石小丽
Original assignee: Huawei Technologies Co Ltd
Current assignee: Huawei Technologies Co Ltd
Priority date: 2021-09-24
Filing date: 2021-09-24
Publication date: 2023-03-28
Also published as: WO2023045931A1

Abstract

A network performance abnormity analysis method, a device and a readable storage medium are used for analyzing the abnormity condition of network performance parameters. According to the method and the device, the first device receives the network performance abnormity analysis demand information, analyzes the network performance parameters according to the network performance abnormity analysis demand information, and sends the obtained network performance abnormity analysis result. The network performance anomaly analysis requirement information comprises at least one of information of network performance parameters or network performance anomaly analysis types. The information of the network performance parameter includes at least one of an identification of the network performance parameter or category information of the network performance parameter. The network performance anomaly analysis types comprise: at least one of a network performance anomaly detection analysis, a network performance anomaly root cause analysis, or a network performance anomaly repair recommendation analysis. Therefore, operation and maintenance personnel are not needed to monitor mass information in real time, labor can be saved, and network abnormity analysis can be carried out according to actual requirements of the operation and maintenance personnel.

Description

Network performance abnormity analysis method and device and readable storage medium

Technical Field

The present application relates to the field of network maintenance technologies, and in particular, to a method and an apparatus for analyzing network performance anomalies, and a readable storage medium.

Background

Operator networks have evolved into fifth generation mobile networks (5 g), network architectures have become more flexible (e.g., serving of core networks, central Unit (CU) and Distributed Unit (DU) separation of Radio Access Networks (RANs), flexible network slice customization, etc.), and demands for network performance parameters such as coverage, capacity, rate, mobility, etc. of networks have been continuously raised. The fifth generation mobile network (the 5th generation,5 g) industry is also becoming more and more rich and diverse, and the demands on network performance parameters such as service user delay, call drop rate and the like are also increasing. Operation and maintenance personnel need to monitor massive information in real time to determine whether the network performance parameters of the current network are abnormal, and a large amount of manpower is consumed in the scheme.

Based on this, a solution for analyzing network performance anomaly is needed to monitor network performance parameters.

Disclosure of Invention

The embodiment of the application provides a network performance abnormity analysis method, a device and a readable storage medium, which are used for analyzing the abnormity condition of network performance parameters.

In a first aspect, an embodiment of the present application provides a method for processing a network problem, including:

the first device receives the network performance abnormity analysis demand information; the network performance abnormity analysis requirement information comprises at least one item of information of network performance parameters or network performance abnormity analysis types; the information of the network performance parameters comprises at least one of identification of the network performance parameters or category information of the network performance parameters; the network performance anomaly analysis types comprise: at least one of a network performance anomaly detection analysis, a network performance anomaly root cause analysis, or a network performance anomaly repair recommendation analysis. And the first device analyzes the network performance parameters according to the network performance abnormity analysis demand information to obtain a network performance abnormity analysis result. The first device sends the network performance anomaly analysis result.

In this embodiment of the application, the first device may analyze the network performance parameter and output a network performance anomaly analysis result. Therefore, operation and maintenance personnel are not needed to monitor massive information in real time, and labor can be saved.

In another possible implementation manner, the first device may analyze the network performance parameter according to the network performance anomaly analysis requirement information, so that a more diverse network performance anomaly analysis service may be provided. For example, the operation and maintenance personnel can extract the network performance abnormality analysis requirement information based on the actual requirements of the operation and maintenance personnel, so that the network abnormality analysis result can better meet the actual requirements of the operation and maintenance personnel.

And the network performance anomaly analysis requirement information can comprise one or more network performance parameters, so that the first device can perform network anomaly analysis on the specified network performance parameters and can also determine the operation to be executed according to the network performance anomaly analysis type, thereby reducing the load of the network performance anomaly analysis of the first device and providing an analysis result of the network performance anomaly which is more in line with the actual requirement of operation and maintenance personnel.

In a possible implementation manner, the network performance anomaly analysis requirement information further includes an anomaly threshold corresponding to the network performance parameter and type information of the anomaly threshold. The type information of the anomaly threshold includes static threshold type information or dynamic threshold type information. Because the network performance abnormity analysis requirement information comprises the abnormity threshold value and the type information of the abnormity threshold value, the operation and maintenance personnel can determine the type of the abnormity threshold value of the network performance parameter according to the actual requirement, and thus the first device can provide diversified services which better meet the requirements of the operation and maintenance personnel.

In one possible implementation, in a case that the type information of the anomaly threshold includes static threshold type information, whether the network performance parameter is abnormal is determined according to the anomaly threshold.

In one possible implementation, where the anomaly threshold type information includes dynamic threshold type information, an anomaly threshold update value is determined, and a determination is made as to whether an anomaly in the network performance parameter has occurred based on the anomaly threshold update value. The method can dynamically adjust the abnormal threshold according to the actual situation, and in the actual application, the dynamic change range of the network performance parameters is large, and if the dynamic threshold type is adopted, the network abnormal analysis result which is more in line with the actual application scene can be given.

In a possible implementation, the network performance anomaly requirement information further includes: and object information of network performance anomaly analysis. The object information of the network performance abnormity analysis comprises at least one of the following contents: information of a geographic region; or, network device information. Because the network performance abnormality analysis requirement information includes the object information of the network performance abnormality analysis, the first device may only analyze the area or the network element indicated by the object information of the network performance abnormality analysis, and the scheme may save network analysis load.

In one possible embodiment, the network performance anomaly analysis requirement information further includes at least one of the following: a first trigger condition for performing root cause analysis on the abnormity of the network performance parameters; or, a second trigger condition for providing a repair recommendation for an abnormality occurring in a network performance parameter.

In a possible implementation manner, in the case that the type information of the network performance anomaly analysis comprises the network performance anomaly root cause analysis type and the first trigger condition: performing root cause analysis on the abnormity of the network performance parameters under the condition that the abnormity of the network performance parameters meets the first triggering condition to obtain a root cause analysis result; the network performance anomaly analysis result comprises a root cause analysis result. Since the network performance anomaly analysis requirement information includes the first trigger condition, the first device may not need to perform root cause analysis for all network performance parameter anomalies, and thus, the network load may be reduced.

In a possible implementation manner, in the case that the type information of the network performance anomaly analysis includes the network performance anomaly repair recommendation analysis type and the second trigger condition: determining a repair suggestion according to the abnormal condition of the network performance parameter under the condition that the abnormal condition of the network performance parameter meets a second trigger condition; the network performance abnormity analysis result comprises a root cause analysis result repair suggestion. Since the network performance anomaly analysis requirement information includes the second trigger condition, the first device may not provide a repair suggestion for all the anomalies occurring in the network performance parameters, and thus the network load may be reduced.

In a possible implementation, the network performance anomaly analysis requirement information further includes network performance anomaly analysis statistical information. The network performance anomaly analysis statistical information indicates the content included in the network performance anomaly analysis result. The network performance anomaly analysis statistics include at least one of: the number of cells with abnormal network performance parameters, the number of grids with abnormal network performance parameters, the number of network elements with abnormal network performance parameters, or the number of times of abnormal network performance parameters. Because the network performance anomaly analysis requirement information comprises the network performance anomaly analysis statistical information, the first device can provide diversified services for operation and maintenance personnel, for example, the network performance anomaly analysis result which better meets the actual requirements of the operation and maintenance personnel can be provided for the operation and maintenance personnel.

In a possible implementation manner, before receiving the network performance anomaly analysis request, the method further includes: sending a first message, wherein the first message comprises capability information which indicates the capability information of the network performance abnormity analysis supported by the capability information; the network performance anomaly analysis requirement information is set according to the capability information. In this way, the other device may determine the network performance abnormality analysis requirement information in combination with the capability information, so that the parameter in the network performance abnormality analysis requirement information is set within the range supported by the first device.

In a second aspect, an embodiment of the present application provides a method for analyzing network performance anomaly, in which a second device sends information required for analyzing network performance anomaly. The network performance anomaly analysis requirement information indicates requirements met by analyzing the network performance parameters; the network performance anomaly analysis requirement information comprises at least one of network performance parameter information or network performance anomaly analysis types; the information of the network performance parameters comprises at least one of identification of the network performance parameters or category information of the network performance parameters; the network performance anomaly analysis types comprise: at least one of network performance anomaly detection analysis, network performance anomaly root cause analysis, or network performance anomaly repair recommendation analysis. The second device receives the network performance anomaly analysis result.

In this embodiment, the second device may send information of a network performance anomaly analysis requirement, so that the received network performance anomaly analysis result is more matched with the requirement of the second device. The network performance abnormity analysis requirement information can comprise one or more network performance parameters, and the network performance abnormity analysis type can be appointed, so that the load of network performance abnormity analysis can be reduced, and a network performance abnormity analysis result which better meets the actual requirement of an operation and maintenance worker is provided.

In a possible implementation manner, the network performance anomaly analysis requirement information further includes an anomaly threshold corresponding to the network performance parameter and type information of the anomaly threshold. The type information of the anomaly threshold includes static threshold type information or dynamic threshold type information. The static threshold type information indicates whether the network performance parameter is abnormal or not according to the abnormal threshold. The dynamic threshold type information indicates to determine an update value of the anomaly threshold and to determine whether the network performance parameter is abnormal according to the update value of the anomaly threshold. The first aspect is referred to for related advantages, which are not described in detail herein.

In one possible implementation, the network performance anomaly requirement information further includes: and the object information of the network performance abnormity analysis indicates the data source of the network performance abnormity analysis. The object information of the network performance abnormity analysis comprises at least one of the following contents: information of a geographic region; or, network device information. For related advantages, reference is made to the first aspect, which is not described in detail herein.

In one possible embodiment, the network performance anomaly analysis requirement information further includes at least one of the following: a first trigger condition for performing root cause analysis on the abnormity of the network performance parameters; or, providing a second trigger condition for the repair suggestion for the abnormity of the network performance parameter. The first aspect is referred to for related advantages, which are not described in detail herein.

In a possible implementation, the network performance anomaly analysis requirement information further includes network performance anomaly analysis statistical information. The network performance anomaly analysis statistical information indicates content included in the network performance anomaly analysis result. The network performance anomaly analysis statistics include at least one of: the number of cells with abnormal network performance parameters, the number of grids with abnormal network performance parameters, the number of network elements with abnormal network performance parameters, or the number of times of abnormal network performance parameters. The first aspect is referred to for related advantages, which are not described in detail herein.

In a possible implementation manner, before receiving the network performance anomaly analysis request, the method further includes: the second device receives a first message including capability information indicating capability information of supported network performance anomaly analysis. And the second device determines the network performance abnormity analysis demand information according to the capability information.

In this way, the other device may determine the network performance abnormality analysis requirement information in combination with the capability information, so that the parameter in the network performance abnormality analysis requirement information is set within the range supported by the first device.

In a third aspect, an apparatus is provided that includes a communication unit and a processing unit. The apparatus may be the first apparatus or the second apparatus. The apparatus may perform any of the first to second aspects described above, and any embodiment of any aspect. The communication unit is used to perform functions related to transmission and reception. Optionally, the communication unit comprises a receiving unit and a transmitting unit. In one design, the device is a communication chip, the processing unit may be one or more processors or processor cores, and the communication unit may be an input-output circuit or port of the communication chip.

In another design, the communication unit may be a transmitter and a receiver, or the communication unit may be a transmitter and a receiver.

Optionally, the apparatus further comprises various means operable to perform any of the first to second aspects described above, and any implementation of any aspect.

In a fourth aspect, an apparatus is provided that includes a processor and a memory. The apparatus may be the first apparatus or the second apparatus. Optionally, the apparatus further comprises a transceiver, the memory is used for storing a computer program or instructions, and the processor is used for calling and executing the computer program or instructions from the memory, and when the processor executes the computer program or instructions in the memory, the apparatus is caused to execute any one of the first aspect to the second aspect, and any one implementation manner of any one aspect.

Optionally, the number of the processors is one or more, and the number of the memories is one or more.

Alternatively, the memory may be integrated with the processor, or may be provided separately from the processor.

Optionally, the transceiver may include a transmitter (transmitter) and a receiver (receiver).

In a fifth aspect, an apparatus is provided that includes a processor. The apparatus may be the first apparatus or the second apparatus. The processor is coupled to the memory and is operable to perform any one of the first to second aspects and any one of the embodiments of any one of the aspects. The apparatus may be the first apparatus or the second apparatus. Optionally, the apparatus further comprises a memory. Optionally, the apparatus further comprises a communication interface, the processor being coupled to the communication interface.

In one implementation, where the apparatus is a first apparatus or a second apparatus, the communication interface may be a transceiver, or an input/output interface. Alternatively, the transceiver may be a transceiver circuit. Alternatively, the input/output interface may be an input/output circuit.

In yet another implementation, when the apparatus is a chip or a system of chips of a first apparatus or a second apparatus, the communication interface may be an input/output interface, an interface circuit, an output circuit, an input circuit, a pin or related circuit, etc. on the chip or the system of chips. A processor may also be embodied as a processing circuit or a logic circuit.

In a sixth aspect, a system is provided, which comprises the above first apparatus and second apparatus.

In a seventh aspect, a computer program product is provided, the computer program product comprising: a computer program (which may also be referred to as code, or instructions), which when executed, causes a computer to perform any of the aspects of the first aspect to the second aspect described above, and any implementation of any aspect.

In an eighth aspect, a computer-readable storage medium is provided, which stores a computer program (which may also be referred to as code, or instructions) that, when executed on a computer, causes the computer to perform any of the first to second aspects described above, and any implementation of any of the aspects.

In a ninth aspect, a chip system is provided, which may include a processor. The processor is coupled to the memory and is operable to perform any of the first to second aspects described above, and any implementation of any of the aspects. Optionally, the chip system further comprises a memory. A memory for storing a computer program (also referred to as code, or instructions). A processor for calling and running the computer program from the memory so that the apparatus on which the system-on-chip is installed performs any of the first aspect to the second aspect, and any implementation of any aspect.

In a tenth aspect, there is provided a processing apparatus comprising: interface circuitry and processing circuitry. The interface circuit may include an input circuit and an output circuit. The processing circuitry is configured to receive a signal via the input circuitry and transmit a signal via the output circuitry such that any of the first to second aspects, and any implementation of any aspect, are implemented.

In a specific implementation process, the processing device may be a chip, the input circuit may be an input pin, the output circuit may be an output pin, and the processing circuit may be a transistor, a gate circuit, a flip-flop, various logic circuits, and the like. The input signal received by the input circuit may be received and input by, for example and without limitation, a receiver, the signal output by the output circuit may be output to and transmitted by a transmitter, for example and without limitation, and the input circuit and the output circuit may be the same circuit that functions as the input circuit and the output circuit, respectively, at different times. The specific implementation of the processor and various circuits are not limited in this application.

In yet another implementation, the apparatus may be a part of a device in the first apparatus or the second apparatus, such as an integrated circuit product like a system chip or a communication chip. The interface circuit may be an input/output interface, interface circuit, output circuit, input circuit, pin or related circuit on the chip or system of chips, etc. The processing circuitry may be logic circuitry on the chip.

Drawings

FIG. 1 is a schematic diagram of a possible network performance anomaly analysis method;

FIG. 2a is a schematic diagram of a system architecture according to an embodiment of the present application;

FIG. 2b is a schematic diagram of another system architecture according to an embodiment of the present application;

fig. 3 is an interactive flow diagram of a network anomaly analysis method provided in the present application;

FIG. 4a is a schematic diagram of the relationship between a KPI abnormal intelligent analysis function management object 1 and a KPI abnormal intelligent analysis capability object;

FIG. 4b is a schematic diagram of creating a KPI anomaly intelligence analysis capability object 2 based on FIG. 4 a;

FIG. 4c is a schematic diagram of a possible system architecture according to an embodiment of the present application;

FIG. 5 is an interactive flow chart of another method for analyzing network performance anomaly, which is provided on the basis of FIG. 3;

FIG. 6 is a schematic diagram of an apparatus according to an embodiment of the present disclosure;

FIG. 7 is a schematic structural diagram of another apparatus provided in an embodiment of the present application;

fig. 8 is a schematic structural diagram of another apparatus provided in the embodiment of the present application.

Detailed Description

The embodiments of the present application will be described in detail below with reference to the drawings attached hereto.

The embodiments of the present application can be applied to various mobile communication systems, for example: a New Radio (NR) system, a Long Term Evolution (LTE) system, an advanced long term evolution (LTE-a) system, a future communication system, and other communication systems, which are not limited herein.

Fig. 1 illustrates a system architecture diagram of a possible network performance anomaly analysis method, as shown in fig. 1, including a Cross-Domain management functional unit (Cross Domain MnF) and a Domain management functional unit (Domain MnF). The Domain management function unit (Domain MnF) may analyze network performance and report a network performance anomaly analysis result.

However, there are hundreds or even thousands of network performance parameters in the network, and these network performance parameters are generated on the minute level, and the Domain management function unit (Domain MnF) performs anomaly analysis on all the network performance parameters, which requires huge calculation and analysis capacity. On the other hand, the network performance parameters concerned by the operation and maintenance personnel are different, and in the prior art, the Domain management function unit (Domain MnF) reports all analyzed network performance parameters, so the operation and maintenance personnel also need to check and collect several network performance parameters needed by the operation and maintenance personnel from a large number of obtained network performance parameters. It can be seen that the network performance anomaly analysis method with a single target causes an overload of a Domain management function unit (Domain MnF) on one hand, and cannot meet different requirements from operation and maintenance personnel on the other hand.

In view of the above problem, fig. 2a illustrates a schematic diagram of a system architecture provided in an embodiment of the present application, where, as shown in fig. 2a, the system architecture includes a first device and a second device. In this embodiment, a location where the first device and the second device are connected may be referred to as an interface, and the first device may provide a service for analyzing the network performance anomaly for the second device through the interface. The second device sends a network performance anomaly analysis request to the first device. The first device receives a network performance anomaly analysis request, wherein the network performance anomaly analysis request comprises requirement information, and the requirement information indicates requirements met by network performance anomaly analysis to be executed. The demand information includes information of network performance parameters. And the first device analyzes the network performance parameters according to the demand information to obtain a network performance abnormity analysis result. And the first device sends a network performance abnormity analysis response to the second device, wherein the network performance abnormity analysis response comprises a network performance abnormity analysis result.

It can be seen that, in the embodiment of the present application, the first device may receive the requirement information, and perform the network performance anomaly analysis according to the requirement information. Therefore, operation and maintenance personnel can provide various requirement information based on the actual requirements of the operation and maintenance personnel, and the network anomaly analysis result can be more accordant with the actual requirements of the operation and maintenance personnel.

Fig. 2b is a schematic diagram illustrating another system architecture provided in an embodiment of the present application, which may also be referred to as a network management system, a management architecture, a network architecture, or the like. As shown in fig. 2b, the system architecture includes: the system comprises a service operation unit, a cross-domain management function unit (CD-MnF), a domain management function unit (D-MnF) and a Network Element (NE).

The service operation unit is used for managing one or more cross-domain management functional units. The cross-domain management function unit is used for managing one or more domain management function units. The domain management function may be configured to manage one or more network elements. Each unit will be briefly described below.

(1) And a service operation unit.

The service operation unit may also be referred to as a service support system (BSS) or a Communication Service Management Function (CSMF). The service operation unit can be used for providing functions and management services of charging, settlement, accounting, customer service, business, network monitoring, communication service life cycle management, service intention translation and the like. The business operation unit may include an operator's operation system or a vertical operation technology system (vertical operation technology system).

(2) And managing the functional units across domains.

The cross-domain management function unit may also be referred to as a Network Management Function (NMF). The cross-domain management function may provide one or more of the following functions or management services: the network management system comprises a network life cycle management system, a network deployment system, a network fault management system, a network performance management system, a network configuration management system, a network guarantee system, a network optimization function, a communication service provider network intention (intent-CSP) translation system, a communication service user network intention (intent-CSC) translation system and the like. A network herein may comprise one or more network elements, subnetworks or network slices. For example, the cross-domain management function unit may be a Network Slice Management Function (NSMF), or a Management Data Analysis Function (MDAF), or a self-organization network function (SON-function), or a cross-domain intention management function unit.

It should be noted that, in some deployment scenarios, the cross-domain management function unit may also provide one or several of the following management functions or management services: the method comprises the following steps of managing the life cycle of the sub-network, deploying the sub-network, managing the fault of the sub-network, managing the performance of the sub-network, managing the configuration of the sub-network, ensuring the sub-network, optimizing the sub-network, translating the intention of the sub-network and the like. The sub-network may be composed of a plurality of small sub-networks or a plurality of network slice sub-networks, for example, one access sub-network of the operator includes the access sub-network of device 1 and the access sub-network of device 2.

(3) A domain management function unit.

A domain management function unit, which may also be referred to as a sub Network Management Function (NMF) or a network element management function (network element/function management function), provides one or more of the following functions or management services: the method comprises the following steps of managing the life cycle of a sub-network or a network element, deploying the sub-network or the network element, managing the fault of the sub-network or the network element, managing the performance of the sub-network or the network element, guaranteeing the sub-network or the network element, optimally managing the sub-network or the network element, translating the intention of the sub-network or the network element and the like. A sub-network here comprises one or more network elements. Alternatively, the sub-networks may also comprise one or more sub-networks, i.e. one or more sub-networks constitute a larger coverage sub-network. Alternatively, the sub-networks herein may also include one or more network slicing sub-networks. Wherein a sub-network can be described in at least one of the following ways:

networks of a certain technology domain, such as radio access networks, core networks, transport networks, etc.;

a network of a certain standard, such as a GSM network, an LTE network, a 5G network, etc.;

a network provided by a certain equipment provider, such as a network provided by equipment provider X, etc.;

a network of a certain geographical area, such as a network of a plant a, a network of a city B, etc.

Fig. 2b shows a network of a technical domain as an example, for example, fig. 2a shows each domain management function unit as an example of a wireless access domain management function unit, a core domain management function unit, and a transmission domain management function unit.

(4) A network element.

The network elements are entities providing network services, and include core network elements, radio access network elements, transmission network elements, and the like. As shown in fig. 2b, the radio access network domain management function unit may be configured to manage a radio access network element, the core network element domain management function unit may be configured to manage a core network element, and the transport network domain management function unit may be configured to manage a transport network element.

For example, a core network element may include, but is not limited to, an access and mobility management function (AMF) entity, a Session Management Function (SMF) entity, a Policy Control Function (PCF) entity, a network data analysis function (NWDAF) entity, a network storage function (NRF), a gateway, and the like.

The radio access network elements may include, but are not limited to: various types of base stations (e.g., next generation base station (gNB), evolved Node B (eNB), centralized Control Unit (CUCP), centralized Unit (CU), distributed Unit (DU), centralized user plane unit (CUUP), etc. in this application, the network function NF is also referred to as a network element NE.

In addition, under the service management architecture, there are various deployments of a provider (MnS provider) of a focused management service and a consumer (MnS provider) of the management service, such as: when the management service is a management service provided by the service operation unit, the service operation unit is a management service provider, and other service operator units (for example, a cross-domain management function unit, a domain management function unit, or a network element) may be management service consumers; when the management service is the management service provided by the cross-domain management functional unit, the cross-domain management functional unit is a management service provider, and other service operator units (for example, a service operation unit, a domain management functional unit or a network element) are management service consumers; when the management service is the management service provided by the domain management function unit, the domain management function unit is a management service provider, and the other service operator units (for example, a cross-domain management function unit or a service operation unit or a network element) are management service consumers; when the management service is a management service provided by the network element, the network element is a management service provider, and the other service operator unit (for example, a domain management function unit or a cross-domain management function unit or a service operation unit) is a management service consumer.

The network performance anomaly analysis method provided by the embodiment of the application can be applied to the system architecture shown in fig. 2 b. The first device and the second device in fig. 2a may be deployed in the system architecture in fig. 2b, and when the network performance anomaly analysis method is applied to the system architecture shown in fig. 2b, the first device and the second device in fig. 2a may have different settings in fig. 2b, such as:

1. the second device may be a higher-level management device of the first device, or may be a higher-level management device, which specifically includes the following three cases:

A. the second device is a service operation unit; the first device may be a cross-domain management function, or a network element. The second device may be a service operation unit or a logic unit in the service operation unit (e.g., a chip in the service operation unit), and the first device may be a cross-management function unit or a cross-management function unit, or a domain management function unit or a logic function in the domain management function unit, or an independent network element or a logic function in the network element.

B. The second device is a cross-domain management functional unit; the first apparatus may be a domain management function, or a network element. Wherein, the second device may be a cross-domain management functional unit or a logic unit in the cross-domain management functional unit; the first device may be a domain management function unit, or a logical function in the domain management function unit; alternatively, the first means is a separate network element or a logical function in a network element.

C. The second device is a domain management function unit; the first apparatus may be a network element. Wherein, the second device may be a domain management function unit, or a logic unit in the domain management function unit; the first means may be a separate network element or a logical function in a network element.

It is understood that fig. 2b is described by taking a three-level management device as an example above a network element, and in practical applications, a network architecture may include more or less levels of management devices, and the technical solution provided in this application is also applicable to these network structures.

2. There may also be no upper and lower level restrictions between the second device and the first device, for example, the second device is a provider of the focus management service, and the first device is a consumer of the management service, where the provider of the focus management service and the consumer of the management service refer to the foregoing description. Specifically, the following cases are included:

A. when the second device is a service operation unit, the first device is other than the service operation unit; such as cross-domain management functions, network elements, etc.

B. When the second device is a cross-domain management function unit, the first device may be other units except the cross-domain management function unit, such as a service operation unit, a domain management function unit, a network element, and the like.

C. When the second device is a domain management function unit, the first device may be other units except the domain management function unit, such as a service operation unit, a cross-domain management function unit, a network element, and the like.

D. The second device is a network element, and the first device is other units except the network element, such as a service operation unit, a cross-domain management function unit, a domain management function unit, and the like.

Referring to fig. 3, an interactive flow chart of the network anomaly analysis method provided by the present application is shown, and as shown in fig. 3, the flow chart may be executed by the first device and the second device in fig. 2 a. It should be noted that, in the embodiment of the present application, the first device and the second device may also have other names, for example, the second device may be referred to as a control device, a control module, a network performance abnormality analysis control module, a KPI abnormality intelligent analysis control module, and the like. The first device may be referred to as an execution device, an execution module, a network performance anomaly analysis execution module, a KPI anomaly intelligent analysis execution module, and the like.

As shown in fig. 3, the process includes:

s301, the second device sends the network performance abnormity analysis requirement information to the first device. The network performance anomaly analysis requirement information comprises information of network performance parameters. The information of the network performance parameter includes at least one of an identification of the network performance parameter or category information of the network performance parameter. The network performance anomaly analysis requirement information indicates requirements to be met for analyzing the network performance parameters.

Correspondingly, the first device receives the network performance abnormity analysis demand information from the second device.

And S302, the first device analyzes the network performance parameters according to the network performance abnormity analysis demand information to obtain a network performance abnormity analysis result.

S303, the first device sends the network performance anomaly analysis result.

The first device may return a network performance abnormality analysis result to the second device in S303. In this case, the second device may receive the network performance abnormality analysis result from the first device. In yet another possible implementation, the second device may designate another device (e.g., a third device) as the device that receives the network performance anomaly analysis result, in which case the first device may send the network performance anomaly analysis result to the third device. In the embodiment of the present application, the example in which the first device sends the network performance abnormality analysis result to the second device is shown.

On the other hand, in practical applications, there are hundreds or even thousands of network performance parameters in the network, and these network performance parameters may be generated in minutes, and if all the network performance parameters are analyzed abnormally, huge calculation and analysis capacity is required. And the network performance parameters concerned by different operation and maintenance personnel may be different, and even the network performance parameters concerned by the same operation and maintenance personnel in different network performance anomaly analysis tasks may also be different. Because the first device can analyze the network performance parameters according to the network performance abnormity analysis demand information, more diversified network performance abnormity analysis services can be provided. For example, the operation and maintenance personnel can provide the network performance abnormality analysis demand information based on the actual demands of the operation and maintenance personnel, so that the network abnormality analysis result can be more consistent with the actual demands of the operation and maintenance personnel, the demands of the operation and maintenance personnel can be more met, and the load of network abnormality analysis can be reduced.

The network performance anomaly analysis requirement information in the embodiment of the present application may include multiple parameters, for example, at least one of the following parameters a1, a2, a3, a4, a5, or a6, and the like.

Parameter a1, information of network performance parameters.

The first device in the embodiment of the application is used for analyzing the abnormal condition of the network performance parameter. The network performance parameters in this embodiment may include a network performance measurement parameter (measurement), a network performance key index, a network performance quality index (network performance quality index), a Key Quality Indicator (KQI), a Service Level Aggregation (SLA), and the like.

The network performance parameter indicated by the information of the network performance parameter in the network performance abnormality analysis requirement information is the network performance parameter of the first device that needs to perform the network abnormality analysis. The information of the network performance parameter may indicate one or more network performance parameters. The information of the network performance parameter may comprise at least one of an identification of the network performance parameter or class information of the network performance parameter.

The identifier of the network performance parameter may be, for example, information such as a name of the network performance parameter, and may include at least one of Physical Resource Block (PRB) usage, throughput, delay, or Radio Resource Control (RRC) establishment success rate.

The category information of the network performance parameters may be, for example, coverage, capacity, rate, handover, etc. The class information of a network performance parameter may indicate one or more network performance parameters. For example, if the category information of the network performance parameter is coverage, the information of the network performance parameter indicates one or more network performance parameters under the coverage category. Network performance parameters under coverage categories may include, for example: reference Signal Receiving Power (RSRP), signal to interference-plus-noise ratio (SINR), and the like. For another example, if the category information of the network performance parameter is a rate, the network performance parameter information indicates one or more network performance parameters in the rate category. Such as network performance parameters under rate category, may include, for example: average uplink rate, average downlink rate, etc. For another example, if the category information of the network performance parameter is capacity, the network performance parameter information indicates one or more network performance parameters under the capacity category. Network performance parameters under the capacity category may include, for example: physical Resource Block (PRB) usage, and the like. In this way, the operation and maintenance personnel can specify one or more network performance parameters through the class information of the specified network performance parameters, so that the workload can be saved.

Because the network performance anomaly analysis requirement information comprises the information of the network performance parameters, the first device can only analyze the network performance parameters indicated by the network performance anomaly analysis requirement information, and compared with a scheme of analyzing all the network performance parameters, the scheme can save the network analysis load.

The parameter a2, the abnormal threshold corresponding to the network performance parameter and the type information of the abnormal threshold.

The anomaly threshold may be referred to as an initial threshold, such as KPI initial threshold. The type information of the anomaly threshold includes static threshold type information or dynamic threshold type information.

The static threshold type information indicates whether the network performance parameter is abnormal or not according to the abnormal threshold. In the case where the type information of the anomaly threshold included in the network performance anomaly analysis requirement information includes static threshold type information, the first device may determine whether an anomaly of the network performance parameter occurs according to the anomaly threshold in S302 described above. For example, when the network performance parameter is the RRC establishment success rate and the abnormal threshold of the network performance parameter is 80%, if the first device determines that the RRC establishment success rate is less than 80%, it is determined that the RRC establishment success rate is abnormal. And if the first device judges that the RRC establishment success rate is not less than 80%, determining that the RRC establishment success rate is not abnormal.

The dynamic threshold type information indicates to determine an update value of the anomaly threshold and to determine whether the network performance parameter is abnormal according to the update value of the anomaly threshold. In the case where the anomaly threshold type information included in the network performance anomaly analysis requirement information includes dynamic threshold type information, the first device may determine an anomaly threshold update value in S302 described above, and determine whether an anomaly has occurred in the network performance parameter according to the anomaly threshold update value. For example, the first device may update the anomaly threshold based on an average of the network performance parameter over a period of time. For example, when the network performance parameter is the RRC establishment success rate, the anomaly threshold of the network performance parameter is 80%. The first device determines that the average of the RRC establishment success rates of 10 cells is 85%. If the first device updates the anomaly threshold from 80% to 85%. And then, if the first device judges that the RRC establishment success rate is less than 85%, determining that the RRC establishment success rate is abnormal. And if the first device judges that the RRC establishment success rate is not less than 85%, determining that the RRC establishment success rate is not abnormal. The method can dynamically adjust the abnormal threshold according to the actual situation, and in the actual application, the dynamic change range of the network performance parameters is large, and if the dynamic threshold type is adopted, the network abnormal analysis result which is more in line with the actual application scene can be given.

Because the network performance abnormity analysis requirement information comprises the abnormity threshold value and the type information of the abnormity threshold value, the operation and maintenance personnel can determine the type of the abnormity threshold value of the network performance parameter according to the actual requirement, and thus the first device can provide diversified services which better meet the requirements of the operation and maintenance personnel.

And a parameter a3, object information of network performance anomaly analysis.

The target information of the network performance anomaly analysis may also be understood as a range in which the first device needs to perform the network performance anomaly analysis.

The object information of the network performance abnormity analysis comprises at least one of the following contents: information of a geographic area, or network device information.

For example, the information of the geographic area may be, for example, an administrative area description or a latitude and longitude description, so that the first device may analyze network performance parameters in the geographic area. As another example, the network device information may be, for example, an identifier or a name of one or more network elements, and for example, a network element list may be created, where the network element list may include an identifier or a name of at least one network element, so that the first device may analyze the network performance parameters of the network elements in S302.

Because the network performance anomaly analysis requirement information comprises the object information of the network performance anomaly analysis, the first device can only analyze the area or the network element indicated by the object information of the network performance anomaly analysis, and the scheme can save the network analysis load.

Parameter a4, network performance anomaly analysis type.

The network performance anomaly analysis types comprise: at least one of a network performance anomaly detection analysis, a network performance anomaly root cause analysis, or a network performance anomaly repair recommendation analysis.

When the network performance abnormality analysis requirement information includes the network performance abnormality detection analysis, the first device needs to analyze the network performance parameters in S302, and identify the abnormal network performance parameters. The network performance anomaly analysis results may include identified network performance parameters for which an anomaly occurred.

When the network performance abnormality analysis requirement information includes a network performance abnormality root cause analysis, in the above S302, the first device needs to perform root cause analysis on the abnormality of the network performance parameter to obtain a root cause of the abnormality of the network performance parameter. The root cause of the network performance parameter abnormality may include, for example: parameter configuration issues, software issues, equipment issues, interference issues, increased number of users or increased traffic demand, etc. The root cause of the network performance parameter abnormality can be carried in the network performance abnormality analysis result for reporting, and can also be reported independently. The root cause of the network performance parameter with the abnormality and the reporting time of the network performance abnormality analysis result have no precedence, and the root cause of the network performance parameter with the abnormality can be reported before the network performance abnormality analysis result is reported or after the network performance abnormality analysis result is reported.

When the network performance anomaly analysis requirement information includes the network performance anomaly repair suggestion analysis, in the above S302, the first device needs to analyze the anomaly occurring in the network performance parameter, and provide the repair suggestion of the network performance parameter anomaly. The network performance parameter abnormal repair suggestion can also be understood as KPI abnormal closed-loop suggestion of the network performance parameter. The network performance anomaly analysis results may include repair recommendations for network performance parameter anomalies. The repair suggestion of the network performance parameter abnormality can be carried by the network performance abnormality analysis result for reporting, and can also be independently reported. The repair suggestion with the abnormal network performance parameter and the report time of the network performance abnormal analysis result have no precedence, and the repair suggestion with the abnormal network performance parameter can be reported before the report of the network performance abnormal analysis result or after the report of the network performance abnormal analysis result.

Because the network performance anomaly analysis requirement information comprises the network performance anomaly analysis type, the first device can provide diversified services for operation and maintenance personnel, for example, the first device can provide the operation and maintenance personnel with a network performance anomaly analysis result which is more in line with the actual requirements of the operation and maintenance personnel.

When the network performance anomaly analysis requirement information includes a network performance anomaly root cause analysis, the network performance anomaly analysis requirement information may further include: parameter a4-1: and carrying out a first trigger condition of root cause analysis on the abnormity of the network performance parameters.

In the above S302, the first device may perform root cause analysis on the abnormality of the network performance parameter when the abnormality of the network performance parameter satisfies the first trigger condition, so as to obtain a result of the root cause analysis. The network performance anomaly analysis result comprises a root cause analysis result.

For example, the first trigger condition includes: and RRC establishes a cell number threshold with abnormal success rate. And the first device performs root cause analysis to obtain a result of the root cause analysis under the condition that the number of the cells with abnormal RRC establishment success rate reaches the threshold value of the number of the abnormal cells.

For another example, the first trigger condition includes: and RRC establishes a threshold value of times of abnormal success rate. And the first device performs root cause analysis under the condition that the frequency of the RRC establishment success rate abnormity reaches the frequency threshold value, and obtains the result of the root cause analysis.

Since the network performance anomaly analysis requirement information includes the first trigger condition, the first device may not need to perform root cause analysis for all network performance parameter anomalies, and thus, the network load may be reduced.

When the network performance anomaly analysis requirement information includes the network performance anomaly repair suggestion analysis, the network performance anomaly analysis requirement information may further include: parameter a4-2: and providing a second trigger condition for repair suggestion on the abnormity of the network performance parameters.

In the above S302, the first device may determine the repair suggestion according to the condition that the network performance parameter is abnormal when the condition that the network performance parameter is abnormal satisfies the second trigger condition. The network performance anomaly analysis result comprises repair suggestions.

For example, the second trigger condition includes: and RRC establishes a cell number threshold with abnormal success rate. And the first device determines a repair suggestion according to the abnormal condition of the network performance parameters under the condition that the number of the cells with the abnormal RRC establishment success rate reaches the abnormal cell number threshold. The network performance anomaly analysis result comprises repair suggestions.

For another example, the second trigger condition includes: and RRC establishes a threshold value of the times of the success rate abnormity. And the first device determines a repair suggestion according to the abnormal condition of the network performance parameters under the condition that the abnormal frequency of the RRC establishment success rate reaches the frequency threshold. The network performance anomaly analysis result comprises a repair suggestion.

Since the network performance anomaly analysis requirement information includes the second trigger condition, the first device may not provide a repair suggestion for all the anomalies occurring in the network performance parameters, and thus the network load may be reduced.

And a parameter a5, analyzing statistical information of network performance abnormity.

The network performance anomaly analysis statistical information represents the content that the first device needs to count and report.

The network performance anomaly analysis statistical information comprises at least one of:

the number of cells in which the network performance parameter is abnormal,

the number of grids where network performance parameters are abnormal,

the number of network elements with abnormal network performance parameters, or,

the number of times that network performance parameter anomalies occur.

The network performance anomaly analysis statistical information may also indicate content included in the network performance anomaly analysis result. Such as: when the network performance anomaly analysis statistical information includes the number of cells with network performance parameters having anomalies, the first device performs statistics on the number of cells with network performance parameters having anomalies in the above S302. And the network performance abnormity analysis result comprises the number of the cells with abnormal network performance parameters.

Because the network performance anomaly analysis requirement information comprises the network performance anomaly analysis statistical information, the first device can provide diversified services for operation and maintenance personnel, for example, the network performance anomaly analysis result which better meets the actual requirements of the operation and maintenance personnel can be provided for the operation and maintenance personnel.

Parameter a6, reporting information of network performance anomaly analysis results.

The reported information of the network performance anomaly analysis result may include at least one of the following:

a reporting period, which indicates how often the first device reports the network performance anomaly analysis result in S303;

a reported destination address, where the reported destination address is used to indicate an address of a receiving apparatus of the network performance anomaly analysis result in S303; or a reporting mode, where the reporting mode is used to instruct the first device in S303 to report a form of the network performance anomaly analysis result, for example, a stream report or a file report.

Because the network performance abnormity analysis requirement information comprises the report information, the mode of reporting the network performance abnormity analysis result by the first device can better meet the actual requirements of operation and maintenance personnel.

Prior to S301 above, the first device may transmit a first message to the second device, the first message including the capability information. The capability information indicates capability information of supported network performance anomaly analysis. The first message may also be referred to as a supported KPI analysis type request. The network performance anomaly analysis requirement information is set according to the capability information. The network performance anomaly analysis requirement information may include part or all of the capability information, the network performance anomaly analysis requirement information may also include information other than the capability information, for example, the capability information may not include an anomaly threshold, and the network performance anomaly analysis requirement information may include an anomaly threshold of the network performance parameter.

In yet another possible implementation, before the first device sends the first message to the second device, the second device may send a query request to the first device, where the query request is used to query capability information of network performance anomaly analysis supported by the first device. The first message may be understood as a response message to the query request.

In yet another possible implementation, the first apparatus may not send the first message to the second apparatus, for example, the capability information of the first apparatus may be preset in the second apparatus, or the capability information of the network performance anomaly analysis of the first apparatus may be sent to the second apparatus by another apparatus. Or the second device sets the network performance abnormality analysis requirement information only according to its own requirement (without combining the capability information of the first device), for example, sets the network performance abnormality analysis requirement information only according to the requirement information of the operation and maintenance personnel, and the subsequent first device may perform network performance abnormality analysis based on its own capability information and the network performance abnormality analysis requirement information.

In one possible implementation, a designer may design an Application for network Anomaly analysis (which may be referred to as Key Performance Indicators (KPI) analysis Application (APP)). The application may be installed on a module or device that performs network anomaly analysis, and the application may be updated. The module or device installed with the application may be understood as a first device in the embodiment of the present application, and the first device executes the relevant scheme executed by the first device in fig. 3 by running a program corresponding to the application.

In this embodiment, the first device may determine capability information of the first device itself according to an application for performing network anomaly analysis. In one possible implementation, the first device may create a KPI anomaly intelligent analysis function management object (which may be referred to as KPI analysis function, for example). Further, the first apparatus may create one or more KPI Anomaly intelligent analysis Capability objects (which may be referred to as KPI analysis capabilities, for example) under the KPI Anomaly intelligent analysis function management object. The capability information of the first device may include information in a KPI anomaly intelligence analysis function management object or information in at least one of KPI anomaly intelligence analysis capability objects.

Fig. 4a illustrates a relationship diagram of a KPI abnormal intelligence analysis function management object 1 and a KPI abnormal intelligence analysis capability object. As shown in fig. 4a, KPI anomaly intelligent analysis capability object 1 serves as a sub-object of KPI anomaly intelligent analysis function management object.

The parameters included in the KPI abnormal intelligent analysis function management object may be one or more, an example of the parameters that may be included in the KPI abnormal intelligent analysis function management object is exemplarily shown in table 1, and the KPI abnormal intelligent analysis function management object may include part or all of the parameters shown in table 1.

TABLE 1 parameters that may be included in a KPI anomaly Intelligent analysis function management object

The readable (is ready) in table 1 is used to describe whether the parameter is opened to the caller through the corresponding management interface to read the corresponding value, i.e. whether the caller can obtain the parameter in the management object. Wherein, whether the parameter is readable (is ready) indicates that the parameter is opened to the caller through the corresponding management interface to read the corresponding value, that is, the caller can obtain the parameter in the management object. Wherein, the fact that the parameter is readable (is readable) is F means that the parameter is not opened to the caller through the corresponding management interface to read the corresponding value, that is, the caller cannot acquire the parameter in the management object.

Table 1 shows whether the parameter is configurable (is writable) to describe whether the parameter is opened to the caller through the corresponding management interface to configure the corresponding value, i.e. whether the caller can configure the parameter in the management object. Wherein, whether the configurable (is writable) is T indicates that the parameter is opened to the caller through the corresponding management interface to configure the corresponding value, that is, the caller can configure the parameter in the management object. Wherein, whether the parameter is configurable (is writable) is F, which means that the parameter is not opened to the caller through the corresponding management interface to configure the corresponding value, i.e. the caller cannot configure the parameter in the management object.

The value of KPI anomaly Management Function (MnF) type (MnF type) in table 1 may be a value indicating network performance anomaly analysis.

The KPI anomaly management function identification (MnF id) in table 1 can be used to uniquely identify a KPI anomaly intelligence analysis function instance.

KPI anomaly management function version information (version) in table 1 may be used to describe the version of the network performance anomaly analysis function.

The KPI anomaly management function ANL in table 1 may be one of the following:

an Autonomous level 2 (Autonomous Network level 2) indicating that the first device can identify or detect an abnormality of a Network performance parameter;

autonomous level 3 (Autonomous Network level 3): the first device can carry out delimitation and root cause analysis on the abnormity of the network performance parameter; or

Autonomous level 4 (Autonomous Network level 4): indicating that the first device can give a closed-loop repair recommendation for the abnormality of the network performance parameter.

The parameters included in the KPI abnormality intelligent analysis capability object 1 may be one or more, an example of the parameters that may be included in the KPI abnormality intelligent analysis capability object 1 is exemplarily shown in table 2, and the KPI abnormality intelligent analysis capability object 1 may include part or all of the parameters shown in table 2. The parameters listed in table 2 may be capability information for network performance anomaly analysis supported by the first device in the KPI anomaly intelligent analysis capability object 1.

Table 2 KPI anomaly intelligent analysis capability object 1 parameters that may be included

See table 1 for the relevant description of whether readable (is ready) and configurable (is write) in table 2.

The parameter b1 is information of a network performance parameter (supported KPI information) supported by the first device.

The information of the network performance parameters supported by the first device may comprise at least one of an identification of the network performance parameters or class information of the network performance parameters. The related contents can be referred to the related description of the parameter a1, and are not described in detail herein.

Because the capability information comprises the information of the network performance parameters, the second device can select the network performance parameters meeting the requirements of the operation and maintenance personnel from the capability information and carry the network performance parameters in the network performance abnormity analysis requirement information, so that the network performance abnormity analysis requirement information can be matched with the capability information of the first device and can be matched with the actual requirements of the operation and maintenance personnel, and the scheme can save the network analysis load.

Parameter b2, type information of an abnormal threshold supported by the first device (supported KPI threshold types).

The type information of the anomaly threshold includes static threshold type information or dynamic threshold type information.

The static threshold type information indicates whether the network performance parameter is abnormal or not according to the abnormal threshold. The dynamic threshold type information indicates to determine an update value of an abnormal threshold, and determines whether the network performance parameter is abnormal according to the update value of the abnormal threshold. The related contents can be referred to the related contents of the foregoing parameter b2, and are not described in detail herein.

Because the capability information comprises the abnormal threshold and the type information of the abnormal threshold, the operation and maintenance personnel can select the type of the abnormal threshold which is more in line with the self requirement by combining the capability information, and therefore the first device can provide diversified services which are more in line with the requirements of the operation and maintenance personnel.

Parameter b3, object information (may also be referred to as supported controlled scopes) of the network performance anomaly analysis supported by the first device.

The target information of the network performance abnormality analysis supported by the first device may also be understood as a range in which the first device can perform the network performance abnormality analysis. The object information of the network performance abnormity analysis comprises at least one of the following contents: information of a geographic area, or network device information. The related contents can be referred to the related description of the parameter a3, and are not described in detail here.

Because the capability information comprises the object information of the network performance abnormity analysis, operation and maintenance personnel can select the object information of the network performance abnormity analysis which meets the requirements of the operation and maintenance personnel by combining the capability information, and then the first device can analyze only the area or the network element indicated by the object information of the network performance abnormity analysis, and the scheme can save the network analysis load.

Parameter b4, a network performance anomaly analysis type (supported KPI analysis types) supported by the first device.

The network performance anomaly analysis types comprise: at least one of a network performance anomaly detection analysis, a network performance anomaly root cause analysis, or a network performance anomaly repair recommendation analysis. The related contents can be referred to the related description of the parameter a4, and are not described in detail here.

Because the capability information includes the network performance anomaly analysis type, the first device can provide diversified services for the operation and maintenance personnel, for example, the first device can provide the operation and maintenance personnel with a network performance anomaly analysis result which is more in line with the actual requirements of the operation and maintenance personnel.

Parameter b5, network performance anomaly analysis statistics supported by the first device (also referred to as supported KPI analysis statistics results).

The network performance anomaly analysis statistical information supported by the first device represents the contents which can be counted and reported by the first device.

The network performance anomaly analysis statistics include at least one of:

the number of cells in which the network performance parameter is abnormal,

the number of grids where network performance parameters are abnormal,

the number of network elements in which the network performance parameter is abnormal, or,

the number of times that network performance parameter anomalies occur.

The related content can be referred to the related description of the foregoing parameter a5, and is not described in detail here.

Because the capability information includes the statistical information of the network performance anomaly analysis, the first device can provide various services for the operation and maintenance personnel, for example, the first device can provide the operation and maintenance personnel with a network performance anomaly analysis result which better meets the actual requirements of the operation and maintenance personnel.

In the above S301, the network performance anomaly analysis requirement information is carried in the KPI requirement request, which may also be referred to as KPI information request or KPI info req. The KPI requirement request, which may also be referred to as a KPI anomaly analysis control task management request, may be used to request the first device to create a KPI anomaly analysis control task. In S302, the first device may create a KPI anomaly analysis control task, for example, may create a KPI anomaly intelligent analysis capability object 2 according to the network performance anomaly analysis requirement information. Fig. 4b is a schematic diagram illustrating the creation of a KPI abnormality intelligent analysis capability object 2 on the basis of fig. 4a, as shown in fig. 4b, a KPI abnormality intelligent analysis function management object may comprise a plurality of KPI abnormality intelligent analysis capability objects, and KPI abnormality intelligent analysis capability object 1 and KPI abnormality intelligent analysis capability object 2 are child objects of the KPI abnormality intelligent analysis function management object. The configuration parameters of the KPI anomaly intelligent analysis capability object 2 may be configured according to network performance anomaly analysis requirement information.

In a possible implementation manner, the network performance abnormality analysis requirement information may further include identification information of the KPI abnormality intelligent analysis capability object 2, where the identification information is used to indicate that the network performance abnormality analysis requirement information is for the KPI abnormality intelligent analysis capability object 2, and the configuration parameters of the KPI abnormality intelligent analysis capability object 2 may be determined according to the network performance abnormality analysis requirement information.

Table 3 illustrates several possible illustrations of configuration parameters of the KPI anomaly intelligent analysis capability object 2. The parameters included in the KPI anomaly intelligent analysis capability object 2 may be one or more, an example of parameters that may be included in the KPI anomaly intelligent analysis capability object 2 is illustrated in table 3, and the KPI anomaly intelligent analysis capability object 2 may include some or all of the parameters shown in table 3.

In the embodiment of the present application, the KPI abnormal intelligent analysis capability object 1 or KPI abnormal intelligent analysis capability object 2 may also be referred to as a management object. A management object may be used to describe information in a management system for a managed object or management task. The management object information model can be used as an interaction parameter in the management interface, and a configuration parameter such as shown in table 3 below can be understood as the management object information model. Creating a management object may mean creating management information in a management system, enabling the management system to manage the managed object or perform a management task according to the management information.

Table 3 illustrates exemplary configuration parameters of KPI anomaly Intelligent analysis capability object 2

For further introduction of the embodiment of the present application, fig. 4c exemplarily shows a schematic diagram of a possible system architecture provided by the embodiment of the present application, where the first device in fig. 4c may be the first device in fig. 2a, and the second device in fig. 4c may be the second device in fig. 2 a. As shown in fig. 4c, the second device may acquire the network performance abnormality analysis requirement information. And sending the network performance abnormity analysis requirement information to the first device through the interface. The first device can analyze the capacity of the online network performance, determine an abnormal threshold value according to the information required for analyzing the network performance abnormity, further analyze the network performance parameters in the information required for analyzing the network performance abnormity, and determine that the network performance parameters are abnormal when the value of the network performance parameters meets the requirement of the abnormal threshold value. Further, the first device counts the number of times of abnormality of the network performance parameter and the like. Further, the first device may perform root cause analysis on the abnormality of the network performance parameter, and may also provide a repair suggestion for the abnormality of the network performance. The first device can report the abnormity of the network performance, the root cause of the abnormity of the network performance parameters and the repair suggestion to the second device through the interface, so that the operation and maintenance personnel can see the information through the second device.

In a possible implementation manner, the network performance anomaly analysis type in the network performance anomaly analysis requirement information may include a network performance anomaly root cause analysis, and the network performance anomaly analysis requirement information may include a first trigger condition. In this case, in the above S302, when the first device determines that the first trigger condition is satisfied, the first device may perform root cause analysis on the abnormality of the network performance parameter, and further report a result of the root cause analysis carried with a result of the network performance abnormality analysis, or report the result separately.

Fig. 5 provides an interaction flow diagram of another network performance anomaly analysis method based on fig. 3, as shown in fig. 5:

in a possible implementation manner, the network performance anomaly analysis type in the network performance anomaly analysis requirement information may not include a network performance anomaly root cause analysis, and the network performance anomaly analysis requirement information may not include the first trigger condition. In this case, in S302, the first device may not perform the root cause analysis on the abnormality of the network performance parameter. The flow may include performing the following after S303:

s501, the second device may determine that a task for performing root analysis on the abnormality of the network performance parameter needs to be created.

In this embodiment, after checking the result of the network performance anomaly analysis, the operation and maintenance staff may further input a requirement for creating a task for performing root cause analysis on the anomaly of the network performance parameter in the second device according to an actual requirement, and the second device may determine that a task for performing root cause analysis on the anomaly of the network performance parameter needs to be created. In yet another possible implementation, the second device may determine, according to the network performance abnormality analysis result and a preset third trigger condition, that a task of performing root analysis on the abnormality of the network performance parameter needs to be created when it is determined that data in the network performance abnormality analysis result satisfies the third trigger condition.

S502, the second device sends a first request message for requesting to carry out root cause analysis on the abnormity of the network performance parameters to the first device.

In a possible implementation, the first request message may further include identification information of the KPI abnormal intelligent analysis capability object 2, where the identification information is used to indicate that the first device should perform root cause analysis on the KPI abnormal intelligent analysis capability object 2, that is, indicate that the task of the root cause analysis is the task of the KPI abnormal intelligent analysis capability object 2.

And S503, the first device performs root cause analysis on the abnormity of the network performance parameters based on the first request message to obtain a root cause analysis result.

The root cause analysis result can refer to the related content, and is not described in detail.

S504, the first device sends the result of the root cause analysis to the second device.

In a possible implementation manner, the network performance abnormality analysis type in the network performance abnormality analysis requirement information may include network performance abnormality repair suggestion analysis, and the network performance abnormality analysis requirement information may include a second trigger condition, and when it is determined that the second trigger condition is satisfied, the first device provides a repair suggestion for an abnormality occurring in the network performance, and then carries the repair suggestion on a network performance abnormality analysis result for reporting, or reports the repair suggestion alone.

In another possible implementation, the network performance anomaly analysis type in the network performance anomaly analysis requirement information may not include the network performance anomaly repair suggestion analysis, and the network performance anomaly analysis requirement information may not include the second trigger condition. In this case, in S302, the first device may not perform the repair suggestion analysis on the network performance abnormality. The flow may include performing the following after S303:

s505, the second device may determine that a task for analysis of the network performance anomaly repair recommendation needs to be created.

In this embodiment, after checking the network performance anomaly analysis result, the operation and maintenance staff further inputs a requirement for creating a repair suggestion analysis for the network performance anomaly in the second device according to an actual requirement, and the second device can determine that a task for creating the repair suggestion analysis for the network performance anomaly needs to be created. In another possible implementation, the second device may determine, according to the network performance abnormality analysis result and a preset fourth trigger condition, that a repair suggestion analysis needs to be created for the network performance abnormality when it is determined that data in the network performance abnormality analysis result satisfies the fourth trigger condition.

S506, the second device sends a second request message for requesting a proposed analysis for repairing the network performance anomaly to the first device.

In a possible implementation, the second request message may further include identification information of the KPI abnormal intelligent analysis capability object 2, where the identification information is used to indicate that the first apparatus should perform the repair suggestion analysis on the KPI abnormal intelligent analysis capability object 2, that is, indicate that the task of the repair suggestion analysis is the task of the KPI abnormal intelligent analysis capability object 2.

And S507, the first device carries out repair suggestion analysis on the network performance abnormity based on the second request message to obtain a repair suggestion.

Repair recommendations may include, for example, software reboots, parameter reconfigurations, extensions, etc.

S508, the first device sends a repair recommendation to the second device.

It should be noted that the solutions of S501 to S504 and the solutions of S505 to S508 may exist in the same method flow, or may not exist in one method flow, for example, the network performance anomaly analysis type in the network performance anomaly analysis requirement information may include a network performance anomaly root cause analysis, and the network performance anomaly analysis requirement information may include a first trigger condition. However, the network performance anomaly analysis type in the network performance anomaly analysis requirement information does not include the network performance anomaly repair suggestion analysis, and the network performance anomaly analysis requirement information does not include the second trigger condition. In this case, in the above S302, when the first device determines that the first trigger condition is satisfied, the first device may perform root cause analysis on the abnormality of the network performance parameter, and then report a result of the root cause analysis carried in a result of the network performance abnormality analysis, or report the result separately. After S303, S505-S508 may be performed. There are many combinations, and there is no one list here.

Through the schemes from S501 to S504 and the schemes from S505 to S508, operation and maintenance personnel can more strictly control the timing of root cause analysis and repair suggestion analysis of the first device, so that the analysis of network performance abnormity can be more strictly controlled.

It is understood that, in order to implement the functions of the above-described embodiments, the apparatus includes a corresponding hardware structure and/or software module for performing each function. Those of skill in the art will readily appreciate that the various illustrative elements and method steps described in connection with the embodiments disclosed herein may be implemented as hardware or combinations of hardware and computer software. Whether a function is performed as hardware or computer software driven hardware depends on the particular application scenario and design constraints imposed on the solution.

Fig. 6, 7 and 8 are schematic structural views of possible devices provided by embodiments of the present application. These means can be used to implement the functionality of the first means in the above-described method embodiments and thus also to achieve the advantageous effects provided by the above-described method embodiments. These means can also be used to implement the functionality of the second means in the above-described method embodiments and thus also to achieve the advantageous effects provided by the above-described method embodiments. In the embodiment of the present application, the apparatus may be a first apparatus as in fig. 2a, and may also be a module (e.g. a chip) applied to the first apparatus. In the embodiment of the present application, the apparatus may be a second apparatus as in fig. 2a, and may also be a module (e.g. a chip) applied to the second apparatus.

As shown in fig. 6, the apparatus 1300 includes a processing unit 1310 and a transceiving unit 1320. The apparatus 1300 is configured to implement the functionality of the first apparatus in the method embodiment illustrated in at least one of fig. 3 or fig. 5.

When the apparatus 1300 is used to implement the functionality of the first apparatus in the method embodiments illustrated in at least one of fig. 3 or fig. 5: the processing unit 1310 is configured to perform, via the transceiving unit 1320: receiving network performance abnormity analysis demand information, and analyzing network performance parameters according to the network performance abnormity analysis demand information to obtain a network performance abnormity analysis result; and sending the network performance abnormity analysis result.

When the apparatus 1300 is used to implement the functionality of the first apparatus in the method embodiment illustrated in at least one of fig. 3 or fig. 5: the processing unit 1310 is further configured to perform, by the transceiving unit 1320: and under the condition that the type information of the abnormal threshold comprises static threshold type information, determining whether the network performance parameter is abnormal or not according to the abnormal threshold.

When the apparatus 1300 is used to implement the functionality of the first apparatus in the method embodiments illustrated in at least one of fig. 3 or fig. 5: the processing unit 1310 is further configured to perform, by the transceiving unit 1320: and under the condition that the abnormal threshold type information comprises the dynamic threshold type information, determining an updated value of the abnormal threshold, and determining whether the network performance parameter is abnormal according to the updated value of the abnormal threshold.

When the apparatus 1300 is used to implement the functionality of the first apparatus in the method embodiment illustrated in at least one of fig. 3 or fig. 5: the processing unit 1310 is further configured to perform, by the transceiving unit 1320: under the condition that the type information of the network performance abnormity analysis comprises a network performance abnormity root cause analysis type and a first trigger condition, and under the condition that the network performance parameter abnormity meets the first trigger condition, performing root cause analysis on the abnormity of the network performance parameter to obtain a root cause analysis result; the network performance abnormity analysis result comprises a root cause analysis result.

When the apparatus 1300 is used to implement the functionality of the first apparatus in the method embodiment illustrated in at least one of fig. 3 or fig. 5: the processing unit 1310 is further configured to perform, by the transceiving unit 1320: and under the condition that the type information of the network performance abnormity analysis comprises the network performance abnormity repair suggestion analysis type and a second trigger condition: determining a repair suggestion according to the abnormal condition of the network performance parameter under the condition that the abnormal condition of the network performance parameter meets a second trigger condition; the network performance abnormity analysis result comprises a root cause analysis result repair suggestion.

When the apparatus 1300 is used to implement the functionality of the first apparatus in the method embodiment illustrated in at least one of fig. 3 or fig. 5: sending a first message, wherein the first message comprises capability information, and the capability information indicates capability information of supported network performance anomaly analysis; the network performance anomaly analysis requirement information is set according to the capability information.

As shown in fig. 6, the apparatus 1300 includes a processing unit 1310 and a transceiving unit 1320. The apparatus 1300 is configured to implement the functions of the second apparatus in the method embodiment illustrated in at least one of fig. 3 or fig. 5.

When the apparatus 1300 is used to implement the functionality of a second apparatus in a method embodiment as illustrated in at least one of fig. 3 or fig. 5: the processing unit 1310 is configured to perform, by the transceiving unit 1320: and sending the network performance abnormity analysis requirement information and receiving the network performance abnormity analysis result.

When the apparatus 1300 is used to implement the functionality of a second apparatus in a method embodiment as illustrated in at least one of fig. 3 or fig. 5: the processing unit 1310 is further configured to perform, by the transceiving unit 1320: receiving a first message, the first message including capability information indicating capability information of supported network performance anomaly analysis; and determining the network performance abnormity analysis demand information according to the capability information.

Related contents in the above schemes, and more detailed descriptions of the processing unit 1310 and the transceiver 1320 can be directly obtained by referring to related descriptions in at least one of the method embodiments shown in fig. 3 or fig. 5, which are not described herein again.

As shown in fig. 7, apparatus 1400 includes processing circuitry 1410 and interface circuitry 1420. Processing circuit 1410 and interface circuit 1420 are coupled to each other. It will be appreciated that interface circuit 1420 may be a transceiver or an input-output interface. Optionally, the apparatus 1400 may further include a memory for storing instructions to be executed by the processing circuit or for storing input data required by the processing circuit 1410 to execute the instructions or for storing data generated by the processing circuit 1410 after executing the instructions.

When the apparatus 1400 is used to implement the method shown in at least one of fig. 3 or fig. 5, the processing circuit 1410 is used to implement the functions of the processing unit 1310, and the interface circuit 1420 is used to implement the functions of the transceiving unit 1320.

As shown in fig. 8, the apparatus 1500 includes a processor 1510 and a communication interface 1520. Processor 1510 and communication interface 1520 are coupled to each other. It is to be understood that the communication interface 1520 may be a transceiver or an input-output interface. Optionally, the apparatus 1500 may further include a memory 1530 for storing instructions to be executed by the processor 1510 or for storing input data required by the processor 1510 to execute the instructions or for storing data generated by the processor 1510 after executing the instructions.

When the apparatus 1500 is used to implement the method shown in at least one of fig. 3 or fig. 5, the processor 1510 is used to implement the functions of the processing unit 1310, and the communication interface 1520 is used to implement the functions of the transceiving unit 1320.

When the apparatus 1500 is used to implement the functionality of a first apparatus in a method embodiment as illustrated in at least one of fig. 3 or fig. 5: processor 1510 is configured to perform, via communication interface 1520: receiving network performance abnormity analysis demand information, and analyzing network performance parameters according to the network performance abnormity analysis demand information to obtain a network performance abnormity analysis result; and sending the network performance abnormity analysis result.

When the apparatus 1500 is used to implement the functionality of a second apparatus in a method embodiment as illustrated in at least one of fig. 3 or fig. 5: processor 1510 is configured to perform, via communications interface 1520: and sending the network performance abnormity analysis demand information and receiving a network performance abnormity analysis result.

It is understood that the Processor in the embodiments of the present Application may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, a transistor logic device, a hardware component, or any combination thereof. The general purpose processor may be a microprocessor, but may be any conventional processor.

According to the method provided by the embodiment of the present application, the present application further provides a computer program product, which includes: computer program or instructions which, when run on a computer, cause the computer to perform the method of any one of the embodiments shown in at least one of figures 3 or 5.

According to the method provided by the embodiment of the present application, the present application also provides a computer-readable storage medium storing a program or instructions which, when run on a computer, cause the computer to perform the method of any one of the embodiments shown in at least one of fig. 3 or fig. 5.

According to the method provided by the embodiment of the present application, a chip system is also provided, and the chip system may include a processor. The processor is coupled to the memory and is operable to perform the method of any of the embodiments illustrated in at least one of fig. 3 or fig. 5. Optionally, the chip system further comprises a memory. A memory for storing a computer program (also referred to as code, or instructions). A processor for calling and running the computer program from the memory so that the apparatus with the system on chip installed performs the method of any one of the embodiments shown in at least one of fig. 3 or fig. 5.

According to the method provided by the embodiment of the present application, the present application further provides a system, which includes the aforementioned first device and second device.

The method steps in the embodiments of the present application may be implemented by hardware, or may be implemented by software instructions executed by a processor. The software instructions may be comprised of corresponding software modules that may be stored in Random Access Memory (RAM), flash Memory (flash), read-Only Memory (ROM), programmable Read-Only Memory (prom), erasable Programmable Read-Only Memory (EPROM), electrically Erasable Programmable Read-Only Memory (EPROM), registers, a hard disk, a solid-state drive (SSD), a removable hard disk, a portable Read-Only Memory (CD-ROM), or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor such the processor can read information from, and write information to, the storage medium. Of course, the storage medium may also be integral to the processor. The processor and the storage medium may reside in an ASIC. Additionally, the ASIC may reside in a device. Of course, the processor and the storage medium may reside as discrete components in an apparatus.

In the above embodiments, all or part of the implementation may be realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer programs or instructions. When the computer program or instructions are loaded and executed on a computer, the procedures or functions of the embodiments of the present application are performed in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, a network appliance, a user device, or other programmable apparatus. The computer program or instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another computer readable storage medium, for example, the computer program or instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wire or wirelessly. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that integrates one or more available media. The available media may be magnetic media, such as floppy disks, hard disks, magnetic tape; optical media such as digital video disks; but also semiconductor media such as solid state disks. The computer readable storage medium may be volatile or nonvolatile storage medium, or may include both volatile and nonvolatile types of storage media.

In the embodiments of the present application, unless otherwise specified or conflicting with respect to logic, the terms and/or descriptions in different embodiments have consistency and may be mutually cited, and technical features in different embodiments may be combined to form a new embodiment according to their inherent logic relationship.

In the present application, "a plurality" means two or more. "and/or" describes the association relationship of the associated objects, meaning that there may be three relationships, e.g., a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone, wherein A and B can be singular or plural. In the text description of the present application, the character "/" generally indicates that the preceding and following associated objects are in an "or" relationship; in the formula of the present application, the character "/" indicates that the preceding and following related objects are in a relationship of "division". "including at least one of a, B or C" may mean: comprises A; comprises B; comprises C; comprises A and B; comprises A and C; comprises B and C; including A, B and C.

It is to be understood that the various numerical references referred to in the embodiments of the present application are merely for convenience of description and distinction and are not intended to limit the scope of the embodiments of the present application. The sequence numbers of the above processes do not mean the execution sequence, and the execution sequence of the processes should be determined by the functions and the inherent logic.

Claims

1. A network performance anomaly analysis method is characterized by comprising the following steps:

receiving network performance anomaly analysis demand information; the network performance anomaly analysis requirement information comprises at least one of information of network performance parameters or network performance anomaly analysis types; the information of the network performance parameter comprises at least one of an identification of the network performance parameter or category information of the network performance parameter; the network performance anomaly analysis types comprise: at least one of network performance anomaly detection analysis, network performance anomaly root cause analysis, or network performance anomaly repair suggestion analysis;

analyzing the network performance parameters according to the network performance abnormity analysis demand information to obtain a network performance abnormity analysis result;

and sending the network performance abnormity analysis result.

2. The method according to claim 1, wherein the network performance anomaly analysis requirement information further includes an anomaly threshold corresponding to the network performance parameter and type information of the anomaly threshold;

the type information of the abnormal threshold comprises static threshold type information or dynamic threshold type information;

the analyzing the network performance parameters according to the network performance anomaly analysis demand information to obtain a network performance anomaly analysis result, comprising:

determining whether the network performance parameter is abnormal according to the abnormal threshold under the condition that the type information of the abnormal threshold comprises static threshold type information; or the like, or, alternatively,

and under the condition that the abnormal threshold type information comprises dynamic threshold type information, determining an updated value of the abnormal threshold, and determining whether the network performance parameter is abnormal according to the updated value of the abnormal threshold.

3. The method of claim 1 or 2, wherein the network performance anomaly need information further comprises: object information of network performance anomaly analysis;

the object information of the network performance anomaly analysis comprises at least one of the following contents:

information of a geographic area; or the like, or a combination thereof,

network device information.

4. The method according to any of claims 1-3, wherein the network performance anomaly analysis requirement information further comprises at least one of:

a first trigger condition for performing root cause analysis on the abnormity of the network performance parameters; or the like, or a combination thereof,

and providing a second trigger condition for repair suggestion on the abnormity of the network performance parameter.

5. The method of claim 4, wherein in the case that the type information of the network performance anomaly analysis comprises a network performance anomaly root cause analysis type and the first trigger condition:

the analyzing the network performance parameters according to the network performance abnormity analysis demand information to obtain a network performance abnormity analysis result, comprising:

under the condition that the network performance parameters are abnormal meets the first triggering condition, performing root cause analysis on the abnormality of the network performance parameters to obtain a root cause analysis result; the network performance anomaly analysis result comprises the root cause analysis result.

6. The method according to claim 4 or 5, wherein in case that the type information of the network performance anomaly analysis comprises a network performance anomaly repair proposal analysis type and the second trigger condition:

determining a repair suggestion according to the abnormal condition of the network performance parameter under the condition that the abnormal condition of the network performance parameter meets the second trigger condition; the network performance abnormity analysis result comprises the root cause analysis result repair suggestion.

7. The method of any one of claims 1-6, wherein the network performance anomaly analysis requirement information further comprises network performance anomaly analysis statistics;

the network performance abnormity analysis statistical information indicates the content included in the network performance abnormity analysis result;

the network performance anomaly analysis statistics include at least one of: the number of cells with abnormal network performance parameters, the number of grids with abnormal network performance parameters, the number of network elements with abnormal network performance parameters, or the number of times of abnormal network performance parameters.

8. The method of any of claims 1-7, wherein prior to receiving the network performance anomaly analysis request, further comprising:

sending a first message, the first message including capability information indicating capability information of supported network performance anomaly analysis; the network performance abnormity analysis demand information is set according to the capability information.

9. A network performance anomaly analysis method is characterized by comprising the following steps:

sending network performance abnormity analysis requirement information; the network performance anomaly analysis requirement information indicates requirements met by analysis of the network performance parameters; the network performance anomaly analysis requirement information comprises at least one of information of network performance parameters or network performance anomaly analysis types; the information of the network performance parameter comprises at least one of an identification of the network performance parameter or category information of the network performance parameter; the network performance anomaly analysis types comprise: at least one of network performance anomaly detection analysis, network performance anomaly root cause analysis, or network performance anomaly repair suggestion analysis;

and receiving a network performance abnormity analysis result.

10. The method of claim 9, wherein the network performance anomaly analysis requirement information further includes an anomaly threshold corresponding to the network performance parameter and type information of the anomaly threshold;

the static threshold type information indicates whether the network performance parameter is abnormal or not according to the abnormal threshold;

and the dynamic threshold type information indicates that the abnormal threshold updating value is determined, and whether the network performance parameter is abnormal or not is determined according to the abnormal threshold updating value.

11. The method according to claim 9 or 10, wherein the network performance anomaly need information further comprises: the object information of the network performance abnormity analysis indicates a data source of the network performance abnormity analysis;

information of a geographic region; or the like, or a combination thereof,

network device information.

12. The method according to any of claims 9-11, wherein the network performance anomaly analysis requirement information further comprises at least one of:

a first trigger condition for performing root cause analysis on the abnormity of the network performance parameters; or the like, or, alternatively,

and providing a second trigger condition for repairing the abnormity of the network performance parameter.

13. The method of any of claims 9-12, wherein the network performance anomaly analysis requirement information further comprises network performance anomaly analysis statistics;

the network performance anomaly analysis statistical information indicates the content included in the network performance anomaly analysis result;

14. The method of any of claims 9-13, wherein prior to sending the network performance anomaly analysis request, further comprising:

receiving a first message, the first message comprising capability information indicating capability information of supported network performance anomaly analysis;

and determining the network performance abnormity analysis demand information according to the capability information.

15. The network performance abnormity analysis device is characterized by comprising a processing unit and a transmitting-receiving unit;

the receiving and sending unit is used for receiving and sending data;

the processing unit is configured to perform the method of any one of claims 1 to 8 or the method of any one of claims 9 to 14 via the transceiver unit.

16. A network performance anomaly analysis device comprising a memory and a processor coupled to the memory;

the memory for storing computer programs or instructions;

the processor to execute a computer program or instructions in a memory to cause the communication device to perform the method of any of claims 1-14.

17. A computer-readable storage medium having stored thereon computer-executable instructions that, when invoked by a computer, cause the method of any of claims 1-14 to be performed.