CN112804164B - Flow information generation method and device, electronic equipment and computer readable medium - Google Patents
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- H04L67/1001—Protocols in which an application is distributed across nodes in the network for accessing one among a plurality of replicated servers
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Abstract
The embodiment of the disclosure discloses a traffic information generation method, a traffic information generation device, electronic equipment and a computer readable medium. One embodiment of the method comprises: acquiring interface information of each server interface in a server interface group stored in flow monitoring equipment to obtain an interface information set; acquiring load information of each server interface in a server interface group to obtain a load information set; generating a load optimization coefficient group based on the utilization rate of each processor, the load rate of each network card and the load rate of each interface which are included in the load information set; generating an operation adjusting value group based on each interface grade and each interface score value included by the interface information set, each operation utilization rate and each flow utilization rate included by the load information set; and generating flow value information based on the load optimization coefficient group, the operation adjusting value group and the load information set. According to the implementation mode, the classified settlement is carried out on the flow consumed by different server interfaces, so that the efficiency of the flow settlement is improved.
Description
Technical Field
The embodiment of the disclosure relates to the technical field of computers, in particular to a traffic information generation method, a traffic information generation device, electronic equipment and a computer readable medium.
Background
With the rapid development of computer technology and internet technology, the call volume of the server interface providing services shows a sudden increase trend, and the consumption speed of the flow of each server interface is faster and faster. At present, the flow settlement generally adopts the following modes: and carrying out flow settlement according to the flow consumed by each server interface and the unit flow value attribute value.
However, the above-mentioned method of traffic settlement generally has the following technical problems:
firstly, the traffic consumed by different server interfaces is not classified and settled, so that the settled traffic is not accordant with the actually output traffic, the accuracy of traffic settlement is not high, and the efficiency of traffic settlement is low;
secondly, the influence of flow loss on the utilization rate of the processor, the network card load rate and the interface load rate is not considered, the accuracy of flow settlement is influenced, and the efficiency of flow settlement is low;
thirdly, the flow value attribute value of settlement is not corrected according to the operation utilization rate, the flow utilization rate and the interface score value of different server interfaces, so that the accuracy and efficiency of flow settlement are not high.
Disclosure of Invention
This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter.
Some embodiments of the present disclosure propose a traffic information generation method, apparatus, electronic device, and computer readable medium to solve one or more of the technical problems mentioned in the background section above.
In a first aspect, some embodiments of the present disclosure provide a traffic information generating method, including: the method comprises the steps of obtaining interface information of each server interface in a server interface group stored in flow monitoring equipment to obtain an interface information set, wherein the interface information in the interface information set comprises the following steps: the interface device comprises a server interface name, an interface grade corresponding to the server interface name and an interface score value corresponding to the interface grade; acquiring load information of each server interface in the server interface group to obtain a load information set, wherein the load information in the load information set comprises: the system comprises a server interface, a network card load rate corresponding to the server interface, an interface load rate corresponding to the server interface, a unit time traffic usage amount corresponding to the server interface, a traffic usage rate corresponding to the unit time traffic usage amount, and a unit traffic value attribute value, wherein the server interface is used for running time corresponding to the server interface; generating a load optimization coefficient group based on the utilization rate of each processor, the load rate of each network card and the load rate of each interface which are included in the load information set; generating an operation adjusting value group based on each interface grade and each interface score value included by the interface information set, each operation utilization rate and each flow utilization rate included by the load information set; and generating flow value information based on the load optimization coefficient group, the operation adjusting value group, each operation time length, each unit time flow usage amount and each unit flow value attribute value included in the load information set.
In some embodiments, the generating a load optimization coefficient based on the processor utilization, the network card load rate, and the interface load rate included in each load information of the load information set includes:
generating a load optimization coefficient by the following formula:
wherein the content of the first and second substances,
the load-optimizing factor is represented by a factor,
indicating the processor utilization that the load information includes,
representing a preset processor utilization corresponding to the processor utilization,
representing the network card load rate included in the load information,
representing a preset network card load rate corresponding to the network card load rate,
indicating the interface load rate comprised by said load information,
and representing a preset interface load rate corresponding to the interface load rate.
In some embodiments, the generating a running adjustment value based on the running utilization, the traffic utilization, the interface level, and the non-dimensionalized interface score value comprises:
generating an operating adjustment value by the following formula:
wherein the content of the first and second substances,
the value of the operating adjustment is represented,
the level of the interface is represented by,
a serial number indicating a level of an interface included in the interface information set,
indicating the number of interface levels included in the set of interface information,
indicating that the interface information set includes
The number of levels of the interface is,
the operation utilization rate is represented and the operation utilization rate is represented,
the traffic usage rate is represented by a value representing the traffic usage rate,
representing the non-dimensionalized interface score value.
In some embodiments, the generating flow value information based on the set of load optimization coefficients, the set of operating adjustment values, each operating duration included in the set of load information, each flow usage per unit time, and each flow value per unit value attribute value includes:
and generating a flow total value attribute value through the following formula:
wherein the content of the first and second substances,
the value of the attribute representing the total value of the flow,
a serial number representing a server interface in the set of server interfaces,
representing the number of server interfaces comprised by said set of server interfaces,
representing the second of said set of server interfaces
The running time of each server interface is long,
representing the second of said set of server interfaces
The traffic usage per unit time of the individual server interfaces,
representing the second of said set of server interfaces
Flow per unit time of individual server interfaceThe value attribute value of the unit flow corresponding to the usage amount,
representing the second of said set of server interfaces
The load information of each server interface corresponds to the operation adjustment value,
representing the second of said set of server interfaces
Load optimization coefficients corresponding to the load information of the server interfaces,
indicating a rounding down operation.
In a second aspect, some embodiments of the present disclosure provide a traffic information generating apparatus, including: a first obtaining unit, configured to obtain interface information of each server interface in a server interface group stored by a traffic monitoring device, to obtain an interface information set, where interface information in the interface information set includes: the interface device comprises a server interface name, an interface grade corresponding to the server interface name and an interface score value corresponding to the interface grade; a second obtaining unit, configured to obtain load information of each server interface in the server interface group, to obtain a load information set, where load information in the load information set includes: the system comprises a server interface, a network card load rate corresponding to the server interface, an interface load rate corresponding to the server interface, a unit time traffic usage amount corresponding to the server interface, a traffic usage rate corresponding to the unit time traffic usage amount, and a unit traffic value attribute value, wherein the server interface is used for running time corresponding to the server interface; a first generating unit configured to generate a load optimization coefficient group based on each processor utilization rate, each network card load rate, and each interface load rate included in the load information set; a second generation unit configured to generate a set of operation adjustment values based on each interface level and each interface score value included in the interface information set, each operation utilization rate and each traffic utilization rate included in the load information set; a third generating unit configured to generate flow rate value information based on the set of load optimization coefficients, the set of operation adjustment values, each operation time period included in the set of load information, each unit time flow rate usage amount, and each unit flow rate value attribute value.
In a third aspect, some embodiments of the present disclosure provide an electronic device, comprising: one or more processors; a storage device having one or more programs stored thereon, which when executed by one or more processors, cause the one or more processors to implement the method described in any of the implementations of the first aspect.
In a fourth aspect, some embodiments of the present disclosure provide a computer readable medium on which a computer program is stored, wherein the program, when executed by a processor, implements the method described in any of the implementations of the first aspect.
The above embodiments of the present disclosure have the following advantages: according to the traffic information generation method of some embodiments of the disclosure, the traffic consumed by different server interfaces is classified and settled, so that the accuracy of traffic settlement is improved, and the efficiency of traffic settlement is improved. Specifically, the reason why the efficiency of the traffic settlement is low is that: the traffic consumed by different server interfaces is not classified and settled, so that the settled traffic is not accordant with the actually output traffic, and the accuracy of traffic settlement is not high. Based on this, in the traffic information generation method according to some embodiments of the present disclosure, first, interface information of each server interface in a server interface group stored in the traffic monitoring device is obtained, and an interface information set is obtained. Therefore, the classification condition of the server interface can be known, and a foundation is laid for subsequent classification settlement. And secondly, acquiring load information of each server interface in the server interface group to obtain a load information set. Therefore, data support can be provided for classified settlement of the traffic consumed by different server interfaces. And then, generating a load optimization coefficient group based on the utilization rate of each processor, the load rate of each network card and the load rate of each interface which are included in the load information set. Therefore, the deviation of the flow settlement caused by the flow loss of the processor utilization rate, the network card load rate and the interface load rate can be corrected. And then, generating an operation adjusting value group based on each interface grade and each interface score value included by the interface information set, each operation utilization rate and each flow utilization rate included by the load information set. Therefore, the deviation caused by the flow loss of the operation utilization rate and the flow utilization rate of different server interfaces can be adjusted, and data support is provided for improving the accuracy of flow settlement. And finally, generating flow value information based on the load optimization coefficient group, the operation adjusting value group, each operation time length, each unit time flow usage amount and each unit flow value attribute value included in the load information set. Therefore, the flow consumed by different server interfaces is classified and settled, so that the accuracy of flow settlement is improved, and the efficiency of flow settlement is improved.
Drawings
The above and other features, advantages and aspects of various embodiments of the present disclosure will become more apparent by referring to the following detailed description when taken in conjunction with the accompanying drawings. Throughout the drawings, the same or similar reference numbers refer to the same or similar elements. It should be understood that the drawings are schematic and that elements and elements are not necessarily drawn to scale.
Fig. 1 is a schematic diagram of one application scenario of a traffic information generation method according to some embodiments of the present disclosure;
fig. 2 is a flow diagram of some embodiments of a traffic information generation method according to the present disclosure;
FIG. 3 is a flow diagram of further embodiments of a traffic information generation method according to the present disclosure;
fig. 4 is a schematic structural diagram of some embodiments of a traffic information generating apparatus according to the present disclosure;
FIG. 5 is a schematic structural diagram of an electronic device suitable for use in implementing some embodiments of the present disclosure.
Detailed Description
Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure are shown in the drawings, it is to be understood that the disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the disclosure are for illustration purposes only and are not intended to limit the scope of the disclosure.
It should be noted that, for convenience of description, only the portions related to the related invention are shown in the drawings. The embodiments and features of the embodiments in the present disclosure may be combined with each other without conflict.
It should be noted that the terms "first", "second", and the like in the present disclosure are only used for distinguishing different devices, modules or units, and are not used for limiting the order or interdependence relationship of the functions performed by the devices, modules or units.
It is noted that references to "a", "an", and "the" modifications in this disclosure are intended to be illustrative rather than limiting, and that those skilled in the art will recognize that "one or more" may be used unless the context clearly dictates otherwise.
The names of messages or information exchanged between devices in the embodiments of the present disclosure are for illustrative purposes only, and are not intended to limit the scope of the messages or information.
The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
Fig. 1 is a schematic diagram of an application scenario of a traffic information generation method according to some embodiments of the present disclosure.
In the application scenario of fig. 1, first, the computing device 101 may obtain interface information of each server interface in the server interface group stored by the traffic monitoring device, and obtain an interface information set 102. The interface information in the interface information set 102 includes: the interface device comprises a server interface name, an interface grade corresponding to the server interface name and an interface score value corresponding to the interface grade. Next, the computing device 101 may obtain load information of each server interface in the server interface group to obtain a load information set 103, where the load information in the load information set 103 includes: the system comprises a running time corresponding to the server interface, a running utilization rate corresponding to the running time, a processor utilization rate corresponding to the server interface, a network card load rate corresponding to the server interface, an interface load rate corresponding to the server interface, a unit time flow usage amount corresponding to the server interface, a flow utilization rate corresponding to the unit time flow usage amount, and a unit flow value attribute value. Next, the computing device 101 may generate the load optimization coefficient group 104 based on the respective processor utilization rates, the respective network card load rates, and the respective interface load rates included in the load information set 103 described above. Then, the computing device 101 may generate the operation adjustment value group 105 based on each interface level and each interface score value included in the interface information set 102, each operation utilization rate and each traffic utilization rate included in the load information set. Finally, the computing device 101 may generate the flow value information 106 based on the set of load optimization coefficients 104, the set of operation adjustment values 105, the respective operation time periods, the respective flow usage amounts per unit time, and the respective flow value attribute values included in the set of load information 103.
The computing device 101 may be hardware or software. When the computing device is hardware, it may be implemented as a distributed cluster composed of multiple servers or terminal devices, or may be implemented as a single server or a single terminal device. When the computing device is embodied as software, it may be installed in the hardware devices enumerated above. It may be implemented, for example, as multiple software or software modules to provide distributed services, or as a single software or software module. And is not particularly limited herein.
It should be understood that the number of computing devices in FIG. 1 is merely illustrative. There may be any number of computing devices, as implementation needs dictate.
With continued reference to fig. 2, a flow 200 of some embodiments of a traffic information generation method according to the present disclosure is shown. The method may be performed by the computing device 101 of fig. 1. The flow information generation method comprises the following steps:
In some embodiments, an execution subject of the traffic information generation method (for example, the computing device 101 shown in fig. 1) may obtain, from the terminal device, the interface information of each server interface in the server interface group stored in the traffic monitoring device by a wired connection manner or a wireless connection manner, so as to obtain the interface information set. Wherein, the interface information in the interface information set includes: the interface device comprises a server interface name, an interface grade corresponding to the server interface name and an interface score value corresponding to the interface grade. Here, the interface level may refer to a level of the server interface output traffic. Here, the interface credit value may be a credit value of the rate at which the server interface outputs traffic.
As an example, the interface information set may be:
{ [ Server interface name: XX; interface grade: 2, level; interface rating value: 100 min ];
[ name of server interface: YY; interface grade: grade 1; interface rating value: 90 min ] }.
In some embodiments, the execution subject may obtain load information of each server interface in the server interface group from a terminal device in a wired connection manner or a wireless connection manner, so as to obtain a load information set. Wherein the load information in the load information set includes: the system comprises a running time corresponding to the server interface, a running utilization rate corresponding to the running time, a processor utilization rate corresponding to the server interface, a network card load rate corresponding to the server interface, an interface load rate corresponding to the server interface, a unit time flow usage amount corresponding to the server interface, a flow utilization rate corresponding to the unit time flow usage amount, and a unit flow value attribute value. Here, the operation time duration may be a time duration during which the server interface outputs traffic. Here, the operation utilization rate may be an effective output rate at the time of the server interface operation. Here, the processor utilization may refer to a usage rate of the central processor when the server interface outputs traffic. Here, the network card load rate may refer to a load rate of the network card when the server interface outputs traffic. Here, the interface load rate may refer to a load rate of an interface when the server interface outputs traffic. The value attribute value per unit flow rate may be a value attribute value corresponding to the flow rate output from the server interface per unit time (for example, the flow rate output from the server interface per unit time is 2G/hour, and the corresponding value attribute value is "5 m/G"). Here, the traffic usage rate may refer to a ratio of traffic actually output by the server interface to standard output traffic of the server interface.
As an example, the load information set may be:
{ [ length of run: 2 hours; the operation utilization rate is as follows: 80 percent; processor utilization: 85 percent; the network card load rate is as follows: 90 percent; interface load rate: 90 percent; flow rate usage per unit time: 5G/h; traffic utilization rate: 90 percent; value attribute value per unit flow: 5-membered/G ];
[ length of operation: 3 hours; the operation utilization rate is as follows: 90 percent; processor utilization: 90 percent; the network card load rate is as follows: 95 percent; interface load rate: 90 percent; flow rate usage per unit time: 8G/h; traffic utilization rate: 95 percent; value attribute value per unit flow: 6-membered/G ] }.
And 203, generating a load optimization coefficient group based on the utilization rate of each processor, the load rate of each network card and the load rate of each interface, which are included in the load information set.
In some embodiments, the execution main body may generate a load optimization coefficient based on a processor utilization rate, a network card load rate, and an interface load rate included in each load information in the load information set, and generate the load optimization coefficient by using a formula:
wherein the content of the first and second substances,
representing the load optimization factor.
Indicating the processor utilization comprised by the load information.
Indicating a predetermined processor utilization corresponding to the processor utilization.
And the network card load rate included in the load information is shown.
And representing the preset network card load rate corresponding to the network card load rate.
And the interface load rate included in the load information is shown.
And representing the preset interface load rate corresponding to the interface load rate. Here, the value of the load optimization coefficient may be retained to two significant digits after the decimal point.
As an example, the load information may be: [ length of operation: 2 hours; the operation utilization rate is as follows: 80 percent; processor utilization: 85 percent; the network card load rate is as follows: 90 percent; interface load rate: 90 percent; flow rate usage per unit time: 5G/h; traffic utilization rate: 90 percent; value attribute value per unit flow: 5-membered/G]. Processor utilization including load information
May be "85%". Corresponding to the processor utilization rate
Predetermined processor utilization
May be "90%". Network card load rate included in load information
May be "90%". Corresponding to the network card load rate
Preset network card load rate of
May be "95%". Interface load rate included in load information
May be "90%". Corresponding to the interface load rate
Predetermined interface load rate of
May be "100%". Generating load optimization coefficients by the formula:
as another example, the load information may be: [ length of operation: 3 hours; the operation utilization rate is as follows: 90 percent; processor utilization: 90 percent; the network card load rate is as follows: 95 percent; interface load rate: 90 percent; flow rate usage per unit time: 8G/h; traffic utilization rate: 95 percent; value of unit flowProperty value: 6-membered/G]. Processor utilization including load information
May be "90%". Corresponding to the processor utilization rate
Predetermined processor utilization
May be "95%". Network card load rate included in load information
May be "95%". Corresponding to the network card load rate
Preset network card load rate of
May be "95%". Interface load rate included in load information
May be "90%". Corresponding to the interface load rate
Predetermined interface load rate of
May be "100%". Generating load optimization coefficients by the formula:
thus, a load optimization coefficient group "0.93 is obtained; 0.95".
And 204, generating an operation adjusting value group based on each interface grade and each interface score value included in the interface information set, each operation utilization rate and each flow utilization rate included in the load information set.
In some embodiments, the execution main body may generate an operation adjustment value based on an operation utilization rate and a traffic utilization rate included in each load information of the load information set and an interface level and an interface score value corresponding to the load information, according to the following formula:
wherein the content of the first and second substances,
indicating the running adjustment value.
And indicating the interface level corresponding to the load information.
And representing the operation utilization rate included in the load information.
And indicating the traffic utilization rate included in the load information.
And representing the interface scoring value corresponding to the load information. Here, the value of the operation adjustment value may be retained to two significant digits after the decimal point.
As an example, the load information may be: [ length of operation: 2 hours; the operation utilization rate is as follows: 80 percent; processor utilization: 85 percent; the network card load rate is as follows: 90 percent; interface load rate: 90 percent; flow rate usage per unit time: 5G/h; traffic utilization rate: 90 percent; value attribute value per unit flow: 5-membered/G]. Interface grade corresponding to load information
May be "level 2". Operational utilization of load information included
May be "80%". Traffic usage rate included in load information
May be "90%". The interface rating value corresponding to the load information may be "100". Generating a running adjustment value by the following formula:
as another example, the load information may be: [ length of operation: 3 hours; the operation utilization rate is as follows: 90 percent; processor utilization: 90 percent; the network card load rate is as follows: 95 percent; interface load rate: 90 percent; flow rate usage per unit time: 8G/h; traffic utilization rate: 95 percent; value attribute value per unit flow: 6-membered/G]. Interface grade corresponding to load information
May be "level 1". Operational utilization of load information included
May be "90%". Traffic usage rate included in load information
May be "95%". The interface rating value corresponding to the load information may be "90". Generating a running adjustment value by the following formula:
thus, an operating adjustment value set of "0.9" is obtained; 0.95".
In some embodiments, the execution main body may generate the flow rate value information based on the set of load optimization coefficients, the set of operation adjustment values, each operation time period included in the set of load information, each flow rate usage amount per unit time, and each flow rate value attribute value by various methods.
In some optional implementations of some embodiments, the executing agent may generate the traffic value information by:
firstly, generating a flow total value attribute value through the following formula:
wherein the content of the first and second substances,
representing the value of the total value attribute of the flow.
And the serial number of the server interface in the server interface group is shown.
Indicating the number of server interfaces included in the server interface group.
Indicating the first of the server interface groups
The running time of each server interface.
Indicating the first of the server interface groups
Traffic usage per server interface per unit time.
Indicating the first of the server interface groups
And a unit flow value attribute value corresponding to the unit time flow usage of each server interface.
Indicating the first of the server interface groups
And the operation adjusting value corresponds to the load information of each server interface.
Indicating the first of the server interface groups
And load optimization coefficients corresponding to the load information of the server interfaces.
Indicating a rounding down operation.
As an example, a server interface group includes a number of server interfaces
May be "2". The load optimization coefficient set may be "0.93; 0.95". The set of operating adjustment values may be "0.9; 0.95". The load information set may be { [ run length: 2 hours; the operation utilization rate is as follows: 80 percent; processor utilization: 85 percent; the network card load rate is as follows: 90 percent; interface load rate: 90 percent; flow rate usage per unit time: 5G/h; traffic utilization rate: 90 percent; value attribute value per unit flow: 5-membered/G](ii) a [ length of operation: 3 hours; the operation utilization rate is as follows: 90 percent; processor utilization: 90 percent; the network card load rate is as follows: 95 percent; interface load rate: 90 percent; flow rate usage per unit time: 8G/h; traffic utilization rate: 95 percent; value attribute value per unit flow: 6-membered/G]}. And generating a flow total value attribute value through the following formula:
and secondly, acquiring a user identifier corresponding to the flow monitoring equipment.
In practice, the execution main body may obtain the user identifier corresponding to the traffic monitoring device from the terminal device in a wired connection manner or a wireless connection manner. For example, the user identification may be "BABA".
And thirdly, combining the user identification and the flow total value attribute value to obtain flow value information. In practice, the execution subject may combine the user identifier and the total traffic value attribute value into a binary group, and then use the binary group as traffic value information. For example, a user identification of "BABA" may be combined with a traffic total value attribute value of "185" into a binary group (BABA, 185). The binary (BABA, 185) is then used as traffic value information.
Optionally, the traffic value information is sent to a payment device with a display function associated with the user identifier, so that the payment device performs payment processing.
In some embodiments, the executing entity may send the traffic value information to a payment device with a display function associated with the user identifier, so that the payment device performs payment processing. For example, the traffic value information "(BABA, 185)" may be sent to a payment device "cell phone/computer" with display function associated with the user identification "BABA" described above for payment processing.
The above embodiments of the present disclosure have the following advantages: according to the traffic information generation method of some embodiments of the disclosure, the traffic consumed by different server interfaces is classified and settled, so that the accuracy of traffic settlement is improved, and the efficiency of traffic settlement is improved. Specifically, the reason why the efficiency of the traffic settlement is low is that: the traffic consumed by different server interfaces is not classified and settled, so that the settled traffic is not accordant with the actually output traffic, and the accuracy of traffic settlement is not high. Based on this, in the traffic information generation method according to some embodiments of the present disclosure, first, interface information of each server interface in a server interface group stored in the traffic monitoring device is obtained, and an interface information set is obtained. Therefore, the classification condition of the server interface can be known, and a foundation is laid for subsequent classification settlement. And secondly, acquiring load information of each server interface in the server interface group to obtain a load information set. Therefore, data support can be provided for classified settlement of the traffic consumed by different server interfaces. And then, generating a load optimization coefficient group based on the utilization rate of each processor, the load rate of each network card and the load rate of each interface which are included in the load information set. Therefore, the deviation of the flow settlement caused by the flow loss of the processor utilization rate, the network card load rate and the interface load rate can be corrected. And then, generating an operation adjusting value group based on each interface grade and each interface score value included by the interface information set, each operation utilization rate and each flow utilization rate included by the load information set. Therefore, the deviation caused by the flow loss of the operation utilization rate and the flow utilization rate of different server interfaces can be adjusted, and data support is provided for improving the accuracy of flow settlement. And finally, generating flow value information based on the load optimization coefficient group, the operation adjusting value group, each operation time length, each unit time flow usage amount and each unit flow value attribute value included in the load information set. Therefore, the flow consumed by different server interfaces is classified and settled, so that the accuracy of flow settlement is improved, and the efficiency of flow settlement is improved.
With further reference to fig. 3, a flow 300 of further embodiments of a traffic information generation method according to the present disclosure is shown. The method may be performed by the computing device 101 of fig. 1. The flow information generation method comprises the following steps:
In some embodiments, the specific implementation manner and technical effects of the steps 301 and 302 can refer to the steps 201 and 202 in the embodiments corresponding to fig. 2, which are not described herein again.
And 303, generating a load optimization coefficient based on the processor utilization rate, the network card load rate and the interface load rate which are included in each load information in the load information set, so as to obtain a load optimization coefficient group.
In some embodiments, an executing body (e.g., the computing device 101 shown in fig. 1) of the traffic information generation method may generate the load optimization coefficient according to the following formula based on the processor utilization rate, the network card load rate, and the interface load rate included in each load information in the load information sets:
wherein the content of the first and second substances,
representing the load optimization factor.
Indicating the processor utilization comprised by the load information.
Indicating a predetermined processor utilization corresponding to the processor utilization.
Network card for indicating the load informationThe load factor.
And representing the preset network card load rate corresponding to the network card load rate.
And the interface load rate included in the load information is shown.
And representing the preset interface load rate corresponding to the interface load rate. Here, the value of the load optimization coefficient may be retained to two significant digits after the decimal point.
As an example, the load information may be: [ length of operation: 2 hours; the operation utilization rate is as follows: 80 percent; processor utilization: 85 percent; the network card load rate is as follows: 90 percent; interface load rate: 90 percent; flow rate usage per unit time: 5G/h; traffic utilization rate: 90 percent; value attribute value per unit flow: 5-membered/G]. Processor utilization including load information
May be "85%". Corresponding to the processor utilization rate
Predetermined processor utilization
May be "90%". Network card load rate included in load information
May be "90%". Corresponding to the network card load rate
Preset network card load rate of
May be "95%". Load informationIncluding interface load rate
May be "90%". Corresponding to the interface load rate
Predetermined interface load rate of
May be "100%". Generating a load optimization coefficient by the following formula:
the formula and the related content in step 303 serve as an invention point of the present disclosure, thereby solving a second technical problem submitted in the background art that "the influence of the traffic loss on the processor utilization rate, the network card load rate and the interface load rate is not considered, the accuracy of the traffic settlement is influenced, and the efficiency of the traffic settlement is low". The factors that contribute to the inefficiency of traffic settlement are often as follows: the influence of flow loss on the utilization rate of the processor, the network card load rate and the interface load rate is not considered, and the accuracy of flow settlement is influenced. If the above-mentioned influence factor has been solved just can reach the effect that improves the efficiency of flow settlement. To achieve this effect, the formula in step 303 generates a load optimization coefficient by comparing the processor utilization rate with the preset processor utilization rate, the network card load rate and the preset network card load rate, and the difference between the interface load rate and the preset interface load rate. Therefore, the load difference caused by the traffic loss of the server interface can be corrected and optimized through the load optimization coefficient. Therefore, the influence of flow loss on the utilization rate of the processor, the network card load rate and the interface load rate is solved, the accuracy of flow settlement is improved, and the efficiency of flow settlement is improved.
And 304, generating an operation adjustment value based on the operation utilization rate and the flow utilization rate of each load information in the load information set and the interface level and the interface score value corresponding to the load information to obtain an operation adjustment value group.
In some embodiments, based on an operation utilization rate, a traffic utilization rate, and an interface level and an interface score value corresponding to the load information included in each load information set, the execution main body may generate an operation adjustment value by:
first, the interface scoring value is subjected to non-dimensionalization processing to generate a non-dimensionalized interface scoring value.
As an example, the interface score value may be "100". The interface score value "100" described above may be subjected to a non-dimensionalization process "100/(100 + 90)" to generate a non-dimensionalized interface score value "0.52".
And secondly, generating an operation adjusting value based on the operation utilization rate, the flow utilization rate, the interface level and the dimensionless interface scoring value.
In practice, the second step may generate the operation adjustment value by the following formula:
wherein the content of the first and second substances,
indicating the running adjustment value.
Indicating the interface level described above.
And a serial number indicating the interface level included in the interface information set.
Indicating the number of interface levels included in the interface information set.
Indicating that the interface information set includes
An interface level.
Representing the above-described operational utilization.
Representing the traffic usage rate.
Representing the above-mentioned non-dimensionalized interface score value.
As an example, the load information may be: [ length of operation: 2 hours; the operation utilization rate is as follows: 80 percent; processor utilization: 85 percent; the network card load rate is as follows: 90 percent; interface load rate: 90 percent; flow rate usage per unit time: 5G/h; traffic utilization rate: 90 percent; value attribute value per unit flow: 5-membered/G]. Interface grade corresponding to load information
May be "level 2". Operational utilization of load information included
May be "80%". Traffic usage rate included in load information
May be "90%". The non-dimensionalized interface score value corresponding to the load information may be "0.52". Generating a running adjustment value by the following formula:
the formula and related content in step 304 serve as an invention point of the present disclosure, thereby solving the technical problem mentioned in the background art that "the accuracy and efficiency of traffic settlement are not high because the attribute value of the settled traffic value is not corrected according to the operation utilization rate, the traffic utilization rate and the interface score value of different server interfaces". The impact factors that lead to poor accuracy and efficiency of traffic settlement are often as follows: the settled traffic value attribute value is not corrected according to the operation utilization rate, the traffic utilization rate and the interface score value of different server interfaces, so that the accuracy and efficiency of traffic settlement are not high. If the above-mentioned influence factors are solved, the effect of improving the accuracy and efficiency of the flow rate settlement can be achieved, and in order to achieve this effect, first, the flow rate usage rate is introduced to correct the flow rate outputted per unit time. And then, generating an operation adjusting value through the operation utilization rate and the non-dimensionalization interface scoring value. Therefore, the flow value attribute value of settlement can be corrected according to the operation utilization rate, the flow utilization rate and the interface score value of different server interfaces, so that the error of flow settlement is reduced. Thus, the accuracy and efficiency of traffic settlement are improved.
And 305, generating flow value information based on the load optimization coefficient group, the operation adjusting value group, each operation time length, each unit time flow usage amount and each unit flow value attribute value included in the load information set.
In some embodiments, the specific implementation manner and technical effects of step 305 may refer to step 205 in those embodiments corresponding to fig. 2, and are not described herein again.
As can be seen from fig. 3, compared with the description of some embodiments corresponding to fig. 2, the flow 300 of the traffic information generation method in some embodiments corresponding to fig. 2 may modify the settled traffic value attribute value according to the operation utilization rate, the traffic utilization rate, and the interface score value of different server interfaces, so as to reduce the error of traffic settlement. Thus, the accuracy and efficiency of traffic settlement are improved.
With further reference to fig. 4, as an implementation of the methods shown in the above figures, the present disclosure provides some embodiments of a traffic information generating apparatus, which correspond to those of the method embodiments described above in fig. 2, and which may be applied in various electronic devices.
As shown in fig. 4, the traffic information generation apparatus 400 of some embodiments includes: a first acquisition unit 401, a second acquisition unit 402, a first generation unit 403, a second generation unit 404, and a third generation unit 405. The first obtaining unit 401 is configured to obtain interface information of each server interface in a server interface group stored in the traffic monitoring device, to obtain an interface information set, where the interface information in the interface information set includes: the interface device comprises a server interface name, an interface grade corresponding to the server interface name and an interface score value corresponding to the interface grade; the second obtaining unit 402 is configured to obtain load information of each server interface in the server interface group, and obtain a load information set, where the load information in the load information set includes: the system comprises a server interface, a network card load rate corresponding to the server interface, an interface load rate corresponding to the server interface, a unit time traffic usage amount corresponding to the server interface, a traffic usage rate corresponding to the unit time traffic usage amount, and a unit traffic value attribute value, wherein the server interface is used for running time corresponding to the server interface; the first generating unit 403 is configured to generate a load optimization coefficient group based on each processor utilization rate, each network card load rate, and each interface load rate included in the load information set; the second generating unit 404 is configured to generate a set of operation adjustment values based on the respective interface levels and the respective interface score values included in the interface information sets, the respective operation utilization rates and the respective traffic utilization rates included in the load information sets; the third unit 405 is configured to generate flow value information based on the set of load optimization coefficients, the set of operation adjustment values, the respective operation time periods included in the set of load information, the respective flow usage per unit time, and the respective unit flow value attribute values.
It will be understood that the elements described in the apparatus 400 correspond to various steps in the method described with reference to fig. 2. Thus, the operations, features and resulting advantages described above with respect to the method are also applicable to the apparatus 400 and the units included therein, and will not be described herein again.
Referring now to FIG. 5, a block diagram of an electronic device (e.g., computing device 101 of FIG. 1) 500 suitable for use in implementing some embodiments of the present disclosure is shown. The electronic device shown in fig. 5 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.
As shown in fig. 5, electronic device 500 may include a processing means (e.g., central processing unit, graphics processor, etc.) 501 that may perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM) 502 or a program loaded from a storage means 508 into a Random Access Memory (RAM) 503. In the RAM 503, various programs and data necessary for the operation of the electronic apparatus 500 are also stored. The processing device 501, the ROM 502, and the RAM 503 are connected to each other through a bus 504. An input/output (I/O) interface 505 is also connected to bus 504.
Generally, the following devices may be connected to the I/O interface 505: input devices 506 including, for example, a touch screen, touch pad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; output devices 507 including, for example, a Liquid Crystal Display (LCD), speakers, vibrators, and the like; storage devices 508 including, for example, magnetic tape, hard disk, etc.; and a communication device 509. The communication means 509 may allow the electronic device 500 to communicate with other devices wirelessly or by wire to exchange data. While fig. 5 illustrates an electronic device 500 having various means, it is to be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may alternatively be implemented or provided. Each block shown in fig. 5 may represent one device or may represent multiple devices as desired.
In particular, according to some embodiments of the present disclosure, the processes described above with reference to the flow diagrams may be implemented as computer software programs. For example, some embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In some such embodiments, the computer program may be downloaded and installed from a network via the communication means 509, or installed from the storage means 508, or installed from the ROM 502. The computer program, when executed by the processing device 501, performs the above-described functions defined in the methods of some embodiments of the present disclosure.
It should be noted that the computer readable medium described above in some embodiments of the present disclosure may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer 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 of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, 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. In some embodiments of the disclosure, a computer 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. In some embodiments of the present disclosure, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer 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 computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.
In some embodiments, the clients, servers may communicate using any currently known or future developed network Protocol, such as HTTP (HyperText Transfer Protocol), and may interconnect with any form or medium of digital data communication (e.g., a communications network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the Internet (e.g., the Internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed network.
The computer readable medium may be embodied in the apparatus; or may exist separately without being assembled into the electronic device. The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: the method comprises the steps of obtaining interface information of each server interface in a server interface group stored in flow monitoring equipment to obtain an interface information set, wherein the interface information in the interface information set comprises the following steps: the interface device comprises a server interface name, an interface grade corresponding to the server interface name and an interface score value corresponding to the interface grade; acquiring load information of each server interface in the server interface group to obtain a load information set, wherein the load information in the load information set comprises: the system comprises a server interface, a network card load rate corresponding to the server interface, an interface load rate corresponding to the server interface, a unit time traffic usage amount corresponding to the server interface, a traffic usage rate corresponding to the unit time traffic usage amount, and a unit traffic value attribute value, wherein the server interface is used for running time corresponding to the server interface; generating a load optimization coefficient group based on the utilization rate of each processor, the load rate of each network card and the load rate of each interface which are included in the load information set; generating an operation adjusting value group based on each interface grade and each interface score value included by the interface information set, each operation utilization rate and each flow utilization rate included by the load information set; and generating flow value information based on the load optimization coefficient group, the operation adjusting value group, each operation time length, each unit time flow usage amount and each unit flow value attribute value included in the load information set.
Computer program code for carrying out operations for embodiments of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, 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 computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in some embodiments of the present disclosure may be implemented by software, and may also be implemented by hardware. The described units may also be provided in a processor, and may be described as: a processor includes a first acquisition unit, a second acquisition unit, a first generation unit, a second generation unit, and a third generation unit. Where the names of these units do not in some cases constitute a limitation on the unit itself, for example, the third generating unit may also be described as a "unit that generates flow rate value information based on the set of load optimization coefficients, the set of operation adjustment values, the respective operation time periods included in the set of load information, the respective flow rate usage amounts per unit time, and the respective flow rate value attribute values".
The functions described herein above may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), systems on a chip (SOCs), Complex Programmable Logic Devices (CPLDs), and the like.
The foregoing description is only exemplary of the preferred embodiments of the disclosure and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the invention in the embodiments of the present disclosure is not limited to the specific combination of the above-mentioned features, but also encompasses other embodiments in which any combination of the above-mentioned features or their equivalents is made without departing from the inventive concept as defined above. For example, the above features and (but not limited to) technical features with similar functions disclosed in the embodiments of the present disclosure are mutually replaced to form the technical solution.
Claims (10)
1. A traffic information generation method includes:
the method comprises the steps of obtaining interface information of each server interface in a server interface group stored in flow monitoring equipment to obtain an interface information set, wherein the interface information in the interface information set comprises the following steps: the method comprises the following steps that a server interface name, an interface grade corresponding to the server interface name and an interface score value corresponding to the interface grade are obtained;
acquiring load information of each server interface in the server interface group to obtain a load information set, wherein the load information in the load information set comprises: the operation time corresponding to the server interface, the operation utilization rate corresponding to the operation time, the processor utilization rate corresponding to the server interface, the network card load rate corresponding to the server interface, the interface load rate corresponding to the server interface, the unit time flow usage amount corresponding to the server interface, the flow usage rate corresponding to the unit time flow usage amount, and the unit flow value attribute value;
generating a load optimization coefficient group based on each processor utilization rate, each network card load rate and each interface load rate which are included in the load information set, a preset processor utilization rate corresponding to each processor utilization rate, a preset network card load rate corresponding to each network card load rate and a preset interface load rate corresponding to each interface load rate;
generating an operation adjusting value group based on each interface grade and each interface score value included by the interface information set, each operation utilization rate and each flow utilization rate included by the load information set;
and generating flow value information based on the load optimization coefficient group, the operation adjusting value group, each operation time length, each unit time flow usage amount and each unit flow value attribute value included in the load information set.
2. The method of claim 1, wherein generating load optimization factor sets based on the respective processor utilization, the respective network card loading rate, and the respective interface loading rate included in the set of load information comprises:
and generating a load optimization coefficient based on the processor utilization rate, the network card load rate and the interface load rate which are included by each load information in the load information set, so as to obtain a load optimization coefficient group.
3. The method of claim 1, wherein generating the set of operational adjustment values based on the respective interface levels and the respective interface score values included in the set of interface information, the respective operational utilizations and the respective traffic utilizations included in the set of load information comprises:
and generating an operation adjusting value based on the operation utilization rate and the flow utilization rate of each load information in the load information set and the interface grade value corresponding to the load information to obtain an operation adjusting value group.
4. The method of claim 3, wherein generating the operation adjustment value based on the operation utilization rate, the traffic utilization rate, and the interface level and the interface score value corresponding to the load information included in each load information set comprises:
performing non-dimensionalization on the interface score value to generate a non-dimensionalized interface score value;
generating an operational adjustment value based on the operational utilization, the traffic utilization, the interface level, and the dimensionless interface credit value.
5. The method of claim 1, wherein generating flow value information based on the set of load optimization coefficients, the set of operating adjustment values, the respective operating time periods comprised by the set of load information, the respective flow usage per unit time, and the respective flow value per unit property values comprises:
generating a flow total value attribute value through a formula;
acquiring a user identifier corresponding to the flow monitoring equipment;
and combining the user identification and the flow total value attribute value to obtain flow value information.
6. The method of claim 5, wherein the method further comprises:
and sending the flow value information to a payment device with a display function associated with the user identification for payment processing by the payment device.
7. A traffic information generating apparatus comprising:
a first obtaining unit, configured to obtain interface information of each server interface in a server interface group stored by a traffic monitoring device, to obtain an interface information set, where interface information in the interface information set includes: the method comprises the following steps that a server interface name, an interface grade corresponding to the server interface name and an interface score value corresponding to the interface grade are obtained;
a second obtaining unit, configured to obtain load information of each server interface in the server interface group, to obtain a load information set, where load information in the load information set includes: the operation time corresponding to the server interface, the operation utilization rate corresponding to the operation time, the processor utilization rate corresponding to the server interface, the network card load rate corresponding to the server interface, the interface load rate corresponding to the server interface, the unit time flow usage amount corresponding to the server interface, the flow usage rate corresponding to the unit time flow usage amount, and the unit flow value attribute value;
a first generating unit configured to generate a load optimization coefficient group based on each processor utilization rate, each network card load rate, and each interface load rate included in the load information set, a preset processor utilization rate corresponding to each processor utilization rate, a preset network card load rate corresponding to each network card load rate, and a preset interface load rate corresponding to each interface load rate;
a second generation unit configured to generate a set of operation adjustment values based on each interface level and each interface score value included in the interface information set, each operation utilization rate and each traffic utilization rate included in the load information set;
a third generating unit configured to generate flow value information based on the set of load optimization coefficients, the set of operation adjustment values, each operation time period included in the set of load information, each unit time flow usage amount, and each unit flow value attribute value.
8. The traffic information generation device according to claim 7, wherein the first generation unit is further configured to:
and generating a load optimization coefficient based on the processor utilization rate, the network card load rate and the interface load rate which are included by each load information in the load information set, so as to obtain a load optimization coefficient group.
9. An electronic device, comprising:
one or more processors;
a storage device having one or more programs stored thereon;
when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-6.
10. A computer-readable medium, on which a computer program is stored, wherein the program, when executed by a processor, implements the method of any one of claims 1-6.
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