CN113691406B

CN113691406B - Network quality optimization method and device, storage medium and electronic equipment

Info

Publication number: CN113691406B
Application number: CN202110993800.8A
Authority: CN
Inventors: 邓艳梅; 陈力超; 冯涛; 蔡少佳; 李一晗
Original assignee: China Telecom Corp Ltd
Current assignee: China Telecom Corp Ltd
Priority date: 2021-08-27
Filing date: 2021-08-27
Publication date: 2022-09-02
Anticipated expiration: 2041-08-27
Also published as: CN113691406A

Abstract

The disclosure provides a network quality optimization method and device, a storage medium and electronic equipment, and relates to the technical field of computers. The network quality optimization method comprises the following steps: determining a network quality optimization target user; determining the access network quality difference of a network quality optimization target user according to the network quality detection data; and performing corresponding network optimization on the network quality optimization target user according to the network quality difference of the access network. The method and the device can improve user perception in the aspect of network quality optimization.

Description

Network quality optimization method and device, storage medium and electronic equipment

Technical Field

The present disclosure relates to the field of computer technologies, and in particular, to a network quality optimization method, a network quality optimization device, a storage medium, and an electronic device.

Background

With the wide popularization of internet large-flow applications such as video and live broadcasting, the requirement of broadband users on network quality is higher and higher.

In order to meet the internet access requirements of users, the network quality of the users generally needs to be optimized and upgraded. In the traditional mode, network optimization is only carried out according to the business and communication consumption conditions handled by the user, and the network perception improvement of the user is not obvious.

Disclosure of Invention

The present disclosure provides a network quality optimization method, a network quality optimization device, a storage medium, and an electronic device, thereby overcoming, at least to a certain extent, the problem of poor user perception improvement in the existing network quality optimization method.

According to a first aspect of the present disclosure, there is provided a network quality optimization method, the method including:

determining a network quality optimization target user;

determining the access network quality difference of the network quality optimization target user according to the network quality detection data;

and performing corresponding network optimization on the network quality optimization target user according to the access network quality difference.

In some exemplary embodiments of the present disclosure, the network quality optimization target user includes: speeding up the target user and fault optimization the target user.

In some exemplary embodiments of the present disclosure, determining the network quality optimization target user includes:

acquiring the expected speed-up related data of the current user;

and when the expected speed-up related data of the current user meet a preset rule, determining the current user as the speed-up target user.

In some exemplary embodiments of the present disclosure, the desired speed-up related data comprises: bandwidth, flow, active user number ratio and speed-up success rate.

In some exemplary embodiments of the present disclosure, determining the current user as an acceleration target user when the desired acceleration-related data of the current user satisfies a preset rule includes:

establishing a four-dimensional matrix of the bandwidth, the flow, the ratio of the number of active users and the speed-up success rate;

determining the corresponding bandwidth and the corresponding flow when the ratio of the number of the active users and the speed-up success rate both reach threshold values from the four-dimensional matrix;

and determining the speed-up target user according to the corresponding bandwidth and the flow.

In some exemplary embodiments of the disclosure, the access network quality difference comprises: and access network performance early warning information, intranet quality difference early warning information and terminal mismatching information.

In some exemplary embodiments of the present disclosure, determining the access network quality difference of the network quality optimization target user according to the network quality detection data includes:

and determining the access network performance early warning information according to the PON port flow, the light attenuation size, the CRC error code increment, the PON port light power, the OLT uplink port light power or the PON port support rate of the accelerated target user.

and determining the intranet quality difference early warning information according to the WIFI coverage rate, the WIFI interference strength, the network port plugging condition or the hundred-million single-frequency router of the speed-up target user.

and determining the terminal mismatching information according to the maximum supporting rate of the terminal gateway of the speed-up target user.

In some exemplary embodiments of the present disclosure, determining the network quality optimization target user comprises:

according to the network alarm of the PON, correlating a network resource tree and determining that a network fault affects a user;

and determining the user with the largest failure frequency in a preset period as the failure optimization target user from the users affected by the network failure.

In some exemplary embodiments of the present disclosure, the method further comprises:

determining a key network fault hidden danger list according to the statement information of the fault optimization target user;

and according to the key network fault hidden danger list, remedying the network of the fault optimization target user.

According to a second aspect of the present disclosure, there is provided a network quality optimization apparatus, the apparatus comprising:

the target user determining module is used for determining a target user for optimizing the network quality;

the network quality difference determining module is used for determining the access network quality difference of the network quality optimization target user according to the network quality detection data;

and the network optimization module is used for carrying out corresponding network optimization on the network quality optimization target user according to the access network quality difference.

According to a third aspect of the present disclosure, there is provided a storage medium having stored thereon a computer program which, when executed by a processor, implements the network quality optimization method described above.

According to a fourth aspect of the present disclosure, there is provided an electronic device comprising:

a processing unit;

a storage unit configured to store one or more programs that, when executed by the processor, cause the processor to implement the above-described network quality optimization method.

In the technical solutions provided in some embodiments of the present disclosure, on one hand, by determining a network quality optimization target user, the network quality of the network quality optimization target user can be optimized in a targeted manner, thereby avoiding a problem of high optimization cost caused by large-scale optimization; on the other hand, the access network quality of the network quality optimization target user is determined according to the network quality detection data, and equivalently, network problem points are determined and then network optimization is performed on the network related to the network quality optimization target user.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the disclosure. It is to be understood that the drawings in the following description are merely exemplary of the disclosure, and that other drawings may be derived from those drawings by one of ordinary skill in the art without the exercise of inventive faculty. In the drawings:

FIG. 1 illustrates an exemplary network topology diagram of a network quality optimization scheme of an embodiment of the present disclosure;

fig. 2 schematically illustrates a flow chart of a method of network quality optimization according to an exemplary embodiment of the present disclosure;

FIG. 3 schematically illustrates a flow chart for determining an acceleration target user according to an exemplary embodiment of the present disclosure;

FIG. 4 schematically illustrates a flow chart for determining a target user for fault optimization according to an exemplary embodiment of the present disclosure;

fig. 5 schematically illustrates a block diagram of a network quality optimization apparatus according to an exemplary embodiment of the present disclosure;

fig. 6 schematically shows a block diagram of an electronic device according to an exemplary embodiment of the present disclosure.

Detailed Description

Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the disclosure. One skilled in the relevant art will recognize, however, that the subject matter of the present disclosure can be practiced without one or more of the specific details, or with other methods, components, devices, steps, and the like. In other instances, well-known technical solutions have not been shown or described in detail to avoid obscuring aspects of the present disclosure.

Furthermore, the drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and a repetitive description thereof will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor devices and/or microcontroller devices.

The flow charts shown in the drawings are merely illustrative and do not necessarily include all of the steps. For example, some steps may be decomposed, and some steps may be combined or partially combined, so that the actual execution sequence may be changed according to the actual situation. In addition, all of the following terms "first" and "second" are used for distinguishing purposes only and should not be construed as limiting the present disclosure.

Fig. 1 illustrates an exemplary network topology diagram of a network quality optimization scheme of an embodiment of the present disclosure.

As shown in fig. 1, in the process of accessing to the internet, a broadband user firstly accesses a user device to a home router 101 of the user, and the home router 101 is accessed to an ONU (Optical Network Unit) 102; then, the ONU102 is connected to a PON Port (Passive Optical Network Port) of an OLT (Optical Line Terminal) 104 through one-stage or two-stage OBD (Optical Branching Device) 103, and the OLT104 is connected to an MSE (Multi-Service Edge) 105 through an uplink Port; finally, the MSE105 is connected to the CR (Core Router, metropolitan area network export) 106, and the CR106 is connected to the Internet.

The home router 101 and the ONU102 are used to form a home intranet of a user; the OBD103 and the OLT104 are used for forming an optical access network, and the optical access network is an access network which takes light as a transmission medium, replaces a copper wire and is used for accessing each family; the MSE105 and the CR106 are used to form a metropolitan area network, which implements signal transmission between the internet and the user equipment.

In practical applications, the user device includes, but is not limited to, a smart phone, a tablet computer, a laptop portable computer, a desktop computer, and the like.

It should be understood that the components in the network topology of fig. 1 are merely illustrative. The components can be added, removed or replaced according to the implementation requirement. For example, the OLT may also be an EPON (Ethernet Passive Optical Network). The network quality optimization method provided by the embodiment of the application optimizes related data or equipment in the network topology structure, so that the quality and efficiency of data transmission can be improved, and the user perception degree is improved.

Fig. 2 schematically illustrates a flow chart of a network quality optimization method of an exemplary embodiment of the present disclosure. Referring to fig. 2, the network quality optimization method may include the steps of:

step S220, determining a network quality optimization target user;

step S240, determining the access network quality difference of the network quality optimization target user according to the network quality detection data;

and step S260, carrying out corresponding network optimization on the network quality optimization target user according to the network quality difference of the access network.

According to the network quality optimization method provided by the exemplary embodiment of the disclosure, on one hand, by determining the target user for network quality optimization, the network quality of the target user for network quality optimization can be optimized in a targeted manner, and the problem of high optimization cost caused by large-range optimization is avoided; on the other hand, the access network quality of the network quality optimization target user is determined according to the network quality detection data, namely, network problem points are determined for networks related to the network quality optimization target user, and then network optimization is performed.

The following describes the network quality optimization method in detail with reference to specific network quality detection data and the like:

in step S220, a network quality optimization target user is determined.

In an exemplary embodiment of the present disclosure, according to different user requirements, target users that need to perform network quality optimization may be divided into: speeding up target users and fault optimization target users. The speed-up target user refers to a user with high requirements on network traffic, rate and the like, and the fault optimization target user refers to a user most affected by a network fault, for example, a user most affected by a device fault in an optical network.

For the two different network quality optimization target users, there are two different ways of determining the network quality optimization target user, and next, the determining method and the network optimization way for the two network quality optimization target users will be described separately.

It should be noted that the network quality optimization method provided in the exemplary embodiment of the present disclosure is not only applicable to a broadband network, but also applicable to other networks.

For the speed-up target user, referring to fig. 3, a flowchart for determining the speed-up target user is provided. The specific process of determining the speed-up target user may include:

s301, acquiring the expected speed-up related data of the current user;

and step S303, when the expected speed-up related data of the current user meet a preset rule, determining the current user as a speed-up target user.

In an exemplary embodiment of the present disclosure, the current user refers to a user who has used the network within a preset time period, for example, within a predetermined year, quarter or month. The speed-up related data is expected to refer to data related to increasing network rates, and may be of many kinds.

However, in the exemplary embodiment of the present disclosure, four pieces of relevant data, that is, bandwidth, traffic, active user number ratio, and speed-up success rate, are mainly used as expected speed-up relevant data required by the scheme of the present disclosure, so as to determine a speed-up target user from current users. The active user number ratio refers to the ratio of users using the network to total broadband users in a detection time period; the speed-up success rate refers to the proportion of the users with successful speed-up to the total speed-up users in the historical time period.

In practical applications, the detection time period and the historical time period may be determined according to actual situations, for example, the detection time period may be a month, and the historical time period may be a year or a quarter, which is not limited in particular by the exemplary embodiments of the present disclosure.

Specifically, in the process of determining the speed-up target user, the determination may be performed by judging whether the data related to the speed-up desired by the current user meets a preset rule, where the determining may include:

firstly, establishing a four-dimensional matrix of bandwidth, flow, ratio of active user number and speed-up success rate; for example, a four-dimensional matrix as shown in table 1 is established, where the row of the table is classified into traffic classes, the column of the table is classified into bandwidth classes, and the cells of the table include two data, i.e., active user ratio and speed-up success rate.

TABLE 1

In the process of actually building the four-dimensional matrix, data represented by rows and columns can also be changed, for example, the rows represent bandwidths, and the columns represent traffic; coordinates may also be used to create a four-dimensional matrix of the four parameters, which is not further described herein.

Then, after the four-dimensional matrix is established, the expected speed-up related data meeting the preset rule can be determined from the four-dimensional matrix. In an exemplary embodiment of the present disclosure, the preset rule may be a rule that both the active user number fraction and the speed increase success rate are greater than or equal to a threshold value.

In a specific application process, the threshold values may be the same or different for the active user number proportion and the speed-up success rate. For example, the threshold value of the active user number ratio and the threshold value of the speed increase success rate are both 50%, or the threshold value of the active user number ratio is 60% and the threshold value of the speed increase success rate is 55%. The exemplary embodiment of the present disclosure does not particularly limit the specific values of the threshold of the active user number ratio and the threshold of the speed increase success rate.

Taking the threshold of the active user number ratio and the threshold of the speed-up success rate as 50% as examples, when the active user number ratio and the speed-up success rate are both greater than or equal to 50%, the corresponding bandwidth and flow are the speed-up target user. Taking table 1 as an example, the cells in which the active user ratio and the speed increase success rate are both greater than or equal to 50% are cell 2 × 3 and cell 3 × 2. Wherein, the bandwidth 50M corresponding to the cell 2 x 3 and the corresponding flow are 100G-200G; the bandwidth corresponding to cell 3 x 2 is 100M and the corresponding flow rate is 0G-100G. That is, the speed-up target user can be determined according to the broadband and the traffic size.

In the network quality optimization method provided in the exemplary embodiment of the disclosure, in the process of determining the speed-up target user, based on four parameters of bandwidth, flow, active user number ratio and speed-up success rate, under the condition that the active user number ratio and the speed-up success rate are both high, the speed-up target user is determined by combining corresponding bandwidth and flow; compared with the traditional flow threshold-based determination method, the method can more accurately determine the user with the speed-up requirement, and can perform corresponding upgrading processing such as network speed-up and the like aiming at the speed-up target user, so that the purpose of improving the network perception of the user can be achieved certainly.

In step S240, determining the access network quality difference of the network quality optimization target user according to the network quality detection data; in step S260, the network quality optimization target user is correspondingly optimized according to the quality difference of the access network.

In an exemplary embodiment of the present disclosure, the access network quality difference may include: and access network performance early warning information, intranet quality difference early warning information and terminal mismatching information. The access network performance early warning information may be determined according to a PON port traffic, an optical attenuation, a Cyclic Redundancy Check (CRC) error increment, a PON port optical power, an OLT uplink port optical power, or a PON port support rate of the speed-up target user.

Specifically, when the PON port traffic reaches the PON port congestion critical value, the PON port traffic congestion is determined, the access network quality of the speed-up target user may be determined, and the access network performance warning information may also be sent. The PON port congestion threshold may be a ratio of a rate of the PON port, for example, the PON port congestion threshold may be 70% of the rate of the PON port, and the exemplary embodiment of the present disclosure is not limited in this respect.

Determining the access network performance early warning information according to the light attenuation size may include: and when the light attenuation is large continuously for multiple times, determining that the light attenuation does not reach the standard. The term "light attenuation" refers to a difference between the light emitting power and the light receiving power being greater than a threshold difference, and the light receiving power being less than the threshold power. For example, when the (emission optical power-reception optical power) >28db and the reception optical power < -25db are used, the light attenuation is large; if the light attenuation is large for 15 times continuously, the light attenuation can be determined to be not up to the standard, the quality of the access network of the speed-up target user can be determined at the moment, and the access network performance early warning information can also be sent.

Determining the access network performance warning information according to the CRC error increment may include: if the CRC error code increment of the uplink port of the OLT or the CRC error code increment of the PON port reaches above a critical increment value in one day, CRC error code early warning can be sent to serve as access network performance early warning information, and the access network quality difference of the speed-up target user is determined. The critical increment value may be determined according to actual conditions, for example, the critical increment value may be 10000 or the like. That is, when the CRC error increment of the uplink port of the OLT is more than 10000 or the CRC error increment of the PON port is more than 10000, it is determined that the quality of the access network of the target user is improved. The critical increment value is not particularly limited in the exemplary embodiment of the present disclosure.

Determining the access network performance early warning information according to the optical power of the PON port or the optical power of the uplink port of the OLT may include: and when the optical power of the PON port or the optical power of the uplink port of the OLT is smaller than the optical power threshold, determining to send the optical power early warning of the PON port or the optical power early warning of the uplink port of the OLT so as to determine the access network quality difference of the speed-up target user. The optical power threshold may be determined according to actual device performance, for example, the optical power threshold may be-25.8 db, and when the optical power of the PON port is less than-25.8 db or the optical power of the uplink port on the OLT is less than-25.8 db, the quality difference of the access network of the speed-up target user is determined. The specific value of the optical power threshold is not particularly limited in the exemplary embodiments of the present disclosure.

Determining the access network performance early warning information according to the PON port support rate specifically may include: and determining the supportable user quantity of the PON port according to the lower-hanging user upper limit value determined by the sizes of the uplink bandwidth and the downlink bandwidth of the PON port. For example, for an EPON (Ethernet Passive Optical Network ), assuming that the uplink bandwidth and the downlink bandwidth of the EPON are both 1.25G, the suspended user upper limit value of the EPON may be: a preset number of 500M users, where the preset number may be a number within 10. That is, the supported rate of the EPON is a small number of 500M users.

For example, for a GPON (Gigabit-Capable Passive Optical network, a Passive Optical network with Gigabit function), assuming that the upstream bandwidth of the GPON is 1.25G and the downstream bandwidth is 2.5G, the lower suspended user upper limit value of the GPON may be: the preset number of 1000M users may be a number within 10. That is, the GPON is supported at a rate of a small number of 1000M users.

In an exemplary embodiment of the present disclosure, the intranet quality difference warning information may be determined according to a WIFI coverage rate, a WIFI interference strength, a network port plugging condition, or a hundred mega single-frequency router of the acceleration target user.

Specifically, when the WIFI coverage reaches the signal intensity critical condition, it is determined that the WIFI coverage is low and poor. The signal strength critical condition may be that when the frequency duty ratio of the signal strength of all the wirelessly connected terminals smaller than the strength critical value is greater than the critical frequency, it is determined that the WIFI coverage is poor.

In practical applications, the magnitude of the critical frequency and the critical intensity threshold can be determined according to practical situations. For example, the critical value of the intensity may be-77 dbm, and the critical frequency ratio may be 25%, that is, when the frequency ratio of the signal intensity of all the wirelessly connected terminals less than-77 dbm is greater than 25%, it is determined that the WIFI coverage is poor, and at this time, it may also be determined that the access network quality of the speed-up target user is poor, and the intranet quality warning information may also be sent.

Determining the intranet quality difference early warning information according to the WIFI interference strength can include: the interference strength of the adjacent frequency to the WIFI of the gateway is judged by calculating the signal strength and the signal difference of the adjacent frequency, so that whether the interference strength of the WIFI exceeds a threshold value or not can be determined, intranet quality difference early warning information can be sent when the interference strength exceeds the threshold value, and the access network quality difference of the speed-up target user is determined. The specific threshold value may be determined according to actual situations, and is not particularly limited herein.

Determining the intranet quality difference early warning information according to the network port plugging condition may include: it is determined whether the gigabit router is connected to a hundred megaban LAN port of the gateway. If so, determining that the network port is inserted wrongly, and at the moment, sending the internal network quality difference early warning information to determine the access network quality difference of the speed-up target user.

The intra-network quality difference early warning information is determined according to the hundred mega single-frequency router, and may be determined by the maximum support rate or a supportable router, for example, in the case that the maximum support rate is 100M or only supports a 2.4G single-frequency router, the intra-network quality difference early warning information may be sent, and the access network quality difference of the speed-up target user is determined.

In an exemplary embodiment of the present disclosure, the terminal mismatch information may be determined according to a maximum supported rate of a terminating gateway of an acceleration target user, and if the maximum supported rate of the terminating gateway (i.e., the optical modem) is smaller than a rate of a service provided by the user, for example, the supported rate of the terminating gateway is smaller than 500M, etc., it may be determined that the terminating gateway is a low-energy optical modem, and the terminal mismatch information may be sent, and it is determined that the quality of an access network of the acceleration target user is poor.

In practical application, the network quality differences of different access networks can be determined according to different network settings, and the method is not limited to the three aspects of the listed access network performance early warning information, the intranet quality difference early warning information and the terminal mismatching information. As determined based on the concepts of the disclosed embodiments, fall within the scope of the present application.

After the quality difference of the access network of the speed-up target user is determined, corresponding network optimization can be performed on the network quality optimization target user according to specific early warning information or the quality difference reason. Specifically, in the network optimization process, for the case of PON port traffic congestion, a user at the PON port can be cut into an idle PON port; when the light attenuation does not reach the standard or CRC error code early warning information is sent, network optimization upgrading can be carried out by replacing the equipment optical module; under the condition that the PON port support rate is not enough, the use requirement can be met by upgrading equipment; for the network corresponding to the intranet quality difference early warning information, the network can be optimized by detecting and debugging the intranet of a user, replacing a user router and the like; for the user who sends the terminal mismatching information, the network can be optimized by replacing the user terminal gateway, and the user perception is improved.

With respect to the fault-optimization target user, referring to FIG. 4, a flow chart for determining a fault-optimization target user is provided. The specific process of determining the fault optimization target user may include:

step S401, according to the network alarm of the PON, associating a network resource tree and determining that a network fault affects a user;

and S403, determining the user with the most failure times in a preset period as a failure optimization target user from the users affected by the network failure.

In an exemplary embodiment of the present disclosure, the network alarm of the PON network may include alarm information sent in the case that the OLT is disconnected from the network, the main optical path or the branch optical path is disconnected, and the network resource tree may include a network route of the user, such as the OLT, the main optical path, the first-stage optical splitter, the branch optical path, the second-stage optical splitter, and the like, which the user accesses. The influence of the network fault on the user can be determined according to the network resource tree associated with the user, for example, when an interruption alarm occurs on a main optical path, the primary optical splitter, the branch optical path and the secondary optical splitter connected below the main optical path can be sequentially traced through the network resource tree. And tracing back to the corresponding optical network unit ONU according to the primary optical splitter or the secondary optical splitter, and determining the user affected by the network fault due to the interruption of the main optical path according to the corresponding relation between the optical network unit ONU and the broadband access number which is stored in the system in advance.

Among the determined numerous network fault influence users, the user with the largest number of faults in the preset period can be determined as the fault optimization target user. The preset period may be determined according to actual conditions, for example, the preset period may be a quarter or a month, and the like, and the exemplary embodiment of the present disclosure is not particularly limited thereto.

After the fault optimization target user is determined, a key network fault hidden danger list can be determined according to statement information of the fault optimization target user; and according to the key network fault hidden danger list, the network of the fault optimization target user is renovated. The statement information is statement information of the fault work statement, and belongs to receipt information of the fault repair personnel, and the statement information contains information such as fault reasons. The fault hidden trouble list includes: and the optical paths of the single route and the double route of the OLT are in the same cable or the same ditch, and the black points of the optical cross connecting box and the like. Wherein, the OLT single-route means that the MSE connected to the OLT has only one optical path, and if the optical path is interrupted, the OLT cannot communicate (referred to as "OLT offline"); if the OLT is a dual-route (two upstream optical paths), one optical path is interrupted, and the other optical path can still communicate, at this time, the communication with the user under the OLT is generally not affected; the optical path 'same cable' refers to two optical paths of double routes, and is placed on the same optical cable (different fiber cores), so that the fault risk is increased, and if the optical cable is interrupted, the two optical paths are interrupted; the optical path is in the same groove, that is, two optical paths of the double route are arranged on two different optical cables, but the two optical cables are arranged in the same groove, and if the two optical cables are subjected to the action of external force, all the optical cables in the whole groove are possibly interrupted, so that the optical path in the same groove is also a fault hidden trouble; the black spot of the optical distribution box includes the mouse trouble, the disordered wiring and other situations of the optical distribution box, which are also hidden troubles of the optical path interruption fault.

In the process of renovating the network of the fault optimization target user, renovation of the OLT dual-route optical path in the same trench or in the same cable, etc. may be included, for example, laying the OLT dual-route optical path in the same trench separately in different trenches, or placing two optical paths placed in the same optical cable separately in different optical cables. The method can also comprise the treatment of black spots and the like of the optical cross-connecting box, and can also carry out specific treatment according to other information in the fault hidden danger list, and the detailed description is omitted here.

According to the network quality optimization method provided by the exemplary embodiment of the disclosure, by respectively determining the speed-up target user and the fault optimization target user, corresponding network optimization is performed on the speed-up target user aiming at the reason of the network quality difference of different access networks of the speed-up target user; the method comprises the steps of determining a key network fault hidden danger list aiming at a fault optimization target user, and renovating the network of the fault optimization target user according to the key network fault hidden danger list, so that users with different requirements can adopt different network optimization modes, the aim of network optimization can be achieved more pertinently, and the aim of saving investment cost is achieved while user perception is effectively improved.

It should be noted that although the various steps of the methods of the present disclosure are depicted in the drawings in a particular order, this does not require or imply that these steps must be performed in this particular order, or that all of the depicted steps must be performed, to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step execution, and/or one step broken down into multiple step executions, etc.

Further, the present exemplary embodiment also provides a network quality optimization apparatus.

Fig. 5 schematically shows a block diagram of a network quality optimization apparatus according to an exemplary embodiment of the present disclosure. Referring to fig. 5, a network quality optimizing apparatus 500 according to an exemplary embodiment of the present disclosure may include a target user determining module 510, a network quality difference determining module 520, and a network optimizing module 530.

Specifically, the target user determination module 510 may be configured to determine a network quality optimization target user; the network quality difference determining module 520 may be configured to determine the access network quality difference of the network quality optimization target user according to the network quality detection data; the network optimization module 530 may be configured to perform corresponding network optimization on the network quality optimization target user according to the network quality difference of the access network.

Since each functional module of the network quality optimization device in the embodiment of the present disclosure is the same as that in the embodiment of the method described above, it is not described herein again.

Furthermore, the above-described figures are merely schematic illustrations of processes included in methods according to exemplary embodiments of the present disclosure, and are not intended to be limiting. It will be readily appreciated that the processes illustrated in the above figures are not intended to indicate or limit the temporal order of the processes. In addition, it is also readily understood that these processes may be performed synchronously or asynchronously, e.g., in multiple modules.

It should be noted that although in the above detailed description several modules or units of the device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functions of two or more modules or units described above may be embodied in one module or unit, according to embodiments of the present disclosure. Conversely, the features and functions of one module or unit described above may be further divided into embodiments by a plurality of modules or units.

In an exemplary embodiment of the present disclosure, an electronic device capable of implementing the above method is also provided.

As will be appreciated by one skilled in the art, aspects of the present invention may be embodied as a system, method or program product. Thus, various aspects of the invention may be embodied in the form of: an entirely hardware embodiment, an entirely software embodiment (including firmware, microcode, etc.) or an embodiment combining hardware and software aspects that may all generally be referred to herein as a "circuit," module "or" system.

An electronic device 600 according to this embodiment of the invention is described below with reference to fig. 6. The electronic device 600 shown in fig. 6 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.

As shown in fig. 6, the electronic device 600 is in the form of a general purpose computing device. The components of the electronic device 600 may include, but are not limited to: the at least one processing unit 610, the at least one memory unit 620, a bus 630 connecting different system components (including the memory unit 620 and the processing unit 610), and a display unit 640.

Wherein the storage unit 620 stores program code that can be executed by the processing unit 610, such that the processing unit 610 performs the steps according to various exemplary embodiments of the present invention described in the above section "exemplary method" of the present specification. For example, the processing unit 610 may execute step S220 as shown in fig. 2, determine a network quality optimization target user; step S240, determining the access network quality difference of a network quality optimization target user according to the network quality detection data; and step S260, carrying out corresponding network optimization on the network quality optimization target user according to the network quality difference of the access network.

The storage unit 620 may include readable media in the form of volatile memory units, such as a random access memory unit (RAM)6201 and/or a cache memory unit 6202, and may further include a read-only memory unit (ROM) 6203.

The memory unit 620 may also include a program/utility 6204 having a set (at least one) of program modules 6205, such program modules 6205 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which, or some combination thereof, may comprise an implementation of a network environment.

Bus 630 may be one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

The electronic device 600 may also communicate with one or more external devices 670 (e.g., keyboard, pointing device, bluetooth device, etc.), with one or more devices that enable a user to interact with the electronic device 600, and/or with any devices (e.g., router, modem, etc.) that enable the electronic device 600 to communicate with one or more other computing devices. Such communication may occur via an input/output (I/O) interface 650. Also, the electronic device 600 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network such as the Internet) via the network adapter 660. As shown, the network adapter 660 communicates with the other modules of the electronic device 600 over the bus 630. It should be appreciated that although not shown in the figures, other hardware and/or software modules may be used in conjunction with the electronic device 600, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.

Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which may be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.

In an exemplary embodiment of the present disclosure, there is also provided a computer readable storage medium having stored thereon a program product capable of implementing the above-described method of the present specification. In some possible embodiments, the various aspects of the invention may also be implemented in the form of a program product comprising program code means for causing a terminal device to carry out the steps according to various exemplary embodiments of the invention described in the above section "exemplary method" of this description, when said program product is run on said terminal device.

According to the program product for realizing the method, the portable compact disc read only memory (CD-ROM) can be adopted, the program code is included, and the program product can be operated on terminal equipment, such as a personal computer. However, the program product of the present invention is not limited in this regard and, in the present document, a readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.

The program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

A computer readable signal medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable signal medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.

Program code embodied on a readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

Program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server. In situations involving remote computing devices, the remote computing devices may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to external computing devices (e.g., through the internet using an internet service provider).

Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.

It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is to be limited only by the terms of the appended claims.

Claims

1. A method for optimizing network quality, the method comprising:

determining a network quality optimization target user;

performing corresponding network optimization on the network quality optimization target user according to the access network quality difference;

wherein the network quality optimization target user comprises: accelerating the target user;

the step of determining the network quality optimization target user comprises the following steps:

acquiring the expected speed-up related data of the current user, wherein the expected speed-up related data comprises: bandwidth, flow, active user number ratio and speed-up success rate;

2. The method of claim 1, wherein the network quality optimization target user further comprises: and (4) fault optimization target users.

3. The method of claim 2, wherein the network quality degradation of the access network comprises: and access network performance early warning information, intranet quality difference early warning information and terminal mismatching information.

4. The method of claim 3, wherein determining the network quality difference of the access network of the network quality optimization target user according to the network quality detection data comprises:

and determining the access network performance early warning information according to the PON port flow, the light attenuation size, the CRC error code increment, the PON port light power, the OLT uplink port light power or the PON port support rate of the speed-up target user.

5. The method of claim 3, wherein determining the network quality difference of the access network of the network quality optimization target user according to the network quality detection data comprises:

6. The method of claim 3, wherein determining the network quality difference of the access network of the network quality optimization target user according to the network quality detection data comprises:

7. The method of claim 2, wherein determining the target user for network quality optimization comprises:

according to the network alarm of the PON, correlating the network resource tree and determining that the network fault affects the user;

8. The method of claim 7, further comprising:

9. An apparatus for network quality optimization, the apparatus comprising:

the network optimization module is used for carrying out corresponding network optimization on the network quality optimization target user according to the network quality difference of the access network;

the target user determining module is configured to obtain data related to an expected speed increase of a current user, where the data related to the expected speed increase includes: bandwidth, flow, active user number ratio and speed-up success rate; establishing a four-dimensional matrix of the bandwidth, the flow, the ratio of the number of active users and the speed-up success rate; determining the corresponding bandwidth and the corresponding flow when the ratio of the number of the active users and the speed-up success rate both reach threshold values from the four-dimensional matrix; and determining the speed-up target user according to the corresponding bandwidth and the flow.

10. A storage medium on which a computer program is stored, which program, when being executed by a processor, is adapted to carry out the network quality optimization method according to any one of claims 1 to 8.

11. An electronic device, comprising:

a processing unit;

a storage unit for storing one or more programs which, when executed by the processing unit, cause the processing unit to implement the network quality optimization method of any one of claims 1 to 8.