CN112688797B - Network line selection method, system, terminal device and computer storage medium - Google Patents
Network line selection method, system, terminal device and computer storage medium Download PDFInfo
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Abstract
The present disclosure provides a network line selection method, a system, a terminal device and a computer readable storage medium, wherein the method comprises: creating a resource calculation model for a plurality of alternative network lines; respectively calculating the resource score of each alternative network line based on the resource calculation model; and selecting the candidate network line with the minimum resource score as the target network line based on the resource score of each candidate network line. The embodiment of the disclosure creates a real-time resource calculation model for the alternative network lines, and selects the most appropriate network line according to the resource calculation model, so that the problem of uneven distribution of the network lines in a peak period can be solved at least, and reliable and stable cloud service is provided.
Description
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to a network line selection method, a network line selection system, a terminal device, and a computer-readable storage medium.
Background
In recent years, the service of a large cloud computing center is rapidly developed, which provides a new challenge for network line scheduling of a data center, and how to solve the problem of uneven network line distribution in a peak period is very important for providing reliable and stable cloud service.
Disclosure of Invention
The present disclosure provides a network line selection method, system, terminal device, and computer-readable storage medium to at least solve the above-mentioned problems.
According to an aspect of the embodiments of the present disclosure, there is provided a network line selection method, including:
creating a resource calculation model for a plurality of alternative network lines;
respectively calculating the resource score of each alternative network line based on the resource calculation model; and the number of the first and second groups,
and selecting the candidate network line with the minimum resource score as the target network line based on the resource score of each candidate network line.
In one embodiment, before creating the resource calculation model for several alternative network lines, the method further includes:
screening a plurality of network lines which accord with preset conditions as alternative network lines according to current flow information after a data center enters a peak period;
the traffic information includes a source IP address, a source port, a destination IP address, and a destination port.
In one embodiment, the creating a resource computation model for a number of alternative network lines includes:
determining a plurality of indexes for calculating resource scores of all the alternative network lines;
respectively distributing weight to each index of each alternative network line to obtain a weight parameter of each index of each alternative network line;
performing dimension conversion on each index of each alternative network line to obtain a dimension parameter of each index of each alternative network line; and the number of the first and second groups,
and creating a resource calculation model for the candidate network lines based on the weight parameters and the dimension parameters.
In one embodiment, after determining several indexes used for calculating the resource score of each alternative network line and before assigning a weight to each index of each alternative network line respectively, the method further includes:
respectively obtaining the current resource condition of each index of each alternative network line, the maximum capacity value of each index of each alternative network line and the average resource condition of each index of all alternative network lines;
the distributing the weight for each index of each alternative network line to obtain the weight parameter of each index of each alternative network line includes:
respectively determining an adjusting factor of each index of each alternative network line based on the current resource condition of each index of each alternative network line and the average resource condition of each index of all alternative network lines; and (c) a second step of,
respectively distributing weight to each index of each alternative network line based on the adjustment factor of each index of each alternative network line to obtain the weight parameter of each index of each alternative network line;
the dimension conversion of each index of each alternative network line respectively comprises the following steps:
and performing dimension conversion on each index of each alternative network line respectively based on the current resource condition of each index of each alternative network line and the maximum capacity value of each index of each alternative network line.
In an embodiment, the adjustment factor of each index of each candidate network line is respectively determined based on the current resource condition of each index of each candidate network line and the average resource condition of each index of all candidate network lines, and is obtained according to the following formula:
the adjusting factor based on each index of each alternative network line distributes weight to each index of each alternative network line respectively to obtain a weight parameter of each index of each alternative network line, and the weight parameter is obtained according to the following formula:
in the formula (I), the compound is shown in the specification,
the weight parameter represents the jth index of the ith alternative network line;
the initial weight parameter of the jth index of the ith alternative network line is constantCounting;
an adjustment factor representing the jth index of the ith alternative network line;
the current resource condition, avg, of the jth index of the ith alternative network line j Representing the average resource condition of j index of all the alternative lines;
in an embodiment, the dimension conversion is performed on each index of each candidate network line, and is obtained according to the following formula:
in the formula (I), the compound is shown in the specification,
dimension parameters of j index of the ith candidate network line,
represents the current resource situation of the jth index of the ith alternative network line,
and the maximum capacity value of the j index of the ith alternative network line is represented.
In one embodiment, the creating a resource calculation model for the candidate network lines based on the weight parameters and the dimension parameters is obtained according to the following formula:
in the formula, S i The resource score of the ith candidate network line is represented, n represents the index item number,
dimension parameters of j index of the ith candidate network line,
and the weight parameter represents the j index of the ith alternative network line.
According to another aspect of the embodiments of the present disclosure, there is provided a network line selection system including:
a model creation module configured to create a resource calculation model for a number of alternative network lines;
a calculation module configured to calculate resource scores of the alternative network lines, respectively, based on the resource calculation model; and the number of the first and second groups,
and the selection module is configured to select the candidate network line with the minimum resource score as the target network line based on the resource score of each candidate network line.
According to still another aspect of the embodiments of the present disclosure, there is provided a terminal device, including a memory and a processor, where the memory stores a computer program, and when the processor runs the computer program stored in the memory, the processor executes the network selection method.
According to yet another aspect of the embodiments of the present disclosure, there is provided a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the processor executes the network selection method.
The technical scheme provided by the embodiment of the disclosure can have the following beneficial effects:
according to the network line selection method provided by the embodiment of the disclosure, a resource calculation model is established for a plurality of alternative network lines; respectively calculating the resource score of each alternative network line based on the resource calculation model; and selecting the candidate network line with the minimum resource score as the target network line based on the resource score of each candidate network line. The embodiment of the disclosure creates a real-time resource calculation model for the alternative network lines, and selects the most appropriate network line according to the resource calculation model, so that the problem of uneven distribution of the network lines in a peak period can be solved at least, and reliable and stable cloud service is provided.
Additional features and advantages of the disclosure will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the disclosure. The objectives and other advantages of the disclosure may be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
Drawings
The accompanying drawings are included to provide a further understanding of the disclosed embodiments and are incorporated in and constitute a part of this specification, illustrate embodiments of the disclosure and together with the example serve to explain the principles of the disclosure and not to limit the disclosure.
Fig. 1 is a schematic flow chart of a network line selection method according to an embodiment of the present disclosure;
fig. 2 is a schematic flow chart of another network line selection method provided in the embodiment of the present disclosure;
fig. 3 is a schematic flow chart of another network line selection method provided in the embodiment of the present disclosure;
fig. 4 is a schematic structural diagram of a network line selection system according to an embodiment of the present disclosure;
fig. 5 is a schematic structural diagram of a terminal device according to an embodiment of the present disclosure.
Detailed Description
To make the objects, technical solutions and advantages of the embodiments of the present disclosure more apparent, specific embodiments of the present disclosure are described below in detail with reference to the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating the present disclosure, are given by way of illustration and explanation only, not limitation.
It should be noted that the terms "first," "second," and the like in the description and claims of the present disclosure and in the above-described drawings are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order; also, the embodiments and features of the embodiments in the present disclosure may be arbitrarily combined with each other without conflict.
In the following description, suffixes such as "module", "component", or "unit" used to denote elements are used only for the convenience of explanation of the present disclosure, and have no specific meaning in themselves. Thus, "module", "component" or "unit" may be used mixedly.
In the related technology, the weights of all indexes of network lines are mainly set according to historical operation and maintenance experience or according to an average method at the initial stage of a system, then the resource condition of each line is calculated, the influence degree of each index on the line resource condition along with the real-time condition is not considered to be different, so that the phenomenon that some indexes of some lines run at full load and some indexes have large resources which are not distributed easily occurs, and the performance of the whole network line is influenced is avoided.
In order to solve the above problem, an embodiment of the present disclosure provides a cloud data center network line selection method, where weights of each index are determined according to a real-time line resource condition, and then a resource score of each line is obtained, so that a selection of a network line can be adjusted according to the real-time condition, a condition of uneven distribution is reduced as much as possible, and a better cloud service is provided.
Referring to fig. 1, fig. 1 is a flowchart illustrating a network line selection method according to an embodiment of the disclosure, including steps S101 to S103.
In step S101, a resource calculation model is created for several alternative network lines.
In this embodiment, a real-time resource calculation model is created for the alternative network line according to the current resource condition of the alternative network line, and an optimal target network line is selected based on the real-time resource calculation model, so as to improve the performance and the utilization rate of the whole network line, thereby solving the problem of uneven distribution of the network line in a peak period and providing reliable and stable cloud service.
In one embodiment, before step S101, the method further includes the following steps:
screening a plurality of network lines which accord with preset conditions as alternative network lines according to current flow information after a data center enters a peak period;
the traffic information includes a source IP address, a source port, a destination IP address, and a destination port. Specifically, each alternative network line may be numbered (L) according to the traffic information described above 1 ，L 2 ，L 3 …，L n )。
It should be noted that, when the data center enters the peak time, a person skilled in the art may determine the peak time according to the actual situation of the data center, for example, a website may determine that the user uses the most (the data transmission amount is the most) at about 6 o ' clock to 9 o ' clock in the evening, and may determine 6 o ' clock as the peak time of the incoming data, which is only taken as an example in the present embodiment.
Further, because the influence of small flow on the network line is limited, in this embodiment, after the data center enters a peak period, the system monitors the flow of the network, and when a large flow occurs in the network, a line scheduling task is initiated again, that is, a resource calculation model is created to select a target network line, and the like, where the large flow may be for a flow greater than 500 kb.
In step S102, respectively calculating resource scores of the alternative network lines based on the resource calculation model; and the number of the first and second groups,
in step S103, the candidate network line having the smallest resource score is selected as the target network line based on the resource score of each candidate network line.
The resource score is a resource score condition calculated based on a resource calculation model, the smaller the resource score is, the minimum resource occupancy rate of the network line is, the smaller the load is, the target network line with the minimum resource score is selected to realize network scheduling, and better cloud service provision can be realized by carrying out data transmission based on the network line.
In this embodiment, a resource calculation model is created, and the score condition of each candidate network line is calculated according to the resource calculation model, so that the candidate network line with the minimum resource is selected as the target network line.
Referring to fig. 2, fig. 2 is a schematic flow chart of a method for selecting a network line according to another embodiment of the present disclosure, where on the basis of the previous embodiment, the present embodiment further exemplifies creation of a resource calculation model, and obtains a real-time resource calculation model by setting a weight parameter and a dimension parameter, specifically, the creation of the resource calculation model for a plurality of candidate network lines (i.e., step S101) includes the following steps S1011 to S1014.
In step S1011, several indexes for calculating resource scores of the respective candidate network lines are determined.
In this embodiment, the plurality of indexes include an average packet number, a flow table size, a port forwarding rate, a network forwarding number, and the like.
In step S1012, a weight is respectively assigned to each index of each alternative network line, so as to obtain a weight parameter of each index of each alternative network line;
specifically, weights are distributed to the indexes of the alternative network lines according to real-time resource conditions of the indexes, the obtained weight parameter user creates a model, and the problems that in the related technology, the performance of the whole network line is affected and the like because some indexes of some lines run at full load and some indexes have large resources which are not distributed are avoided by combining a mode of distributing the weights in a differentiation mode according to actual conditions of the indexes of the alternative network lines.
In step S1013, dimension conversion is performed on each index of each candidate network line, so as to obtain a dimension parameter of each index of each candidate network line.
In this embodiment, since there are four indexes with different dimensions, dimension conversion is required in the actual calculation process, and dimension parameters are set in the model in addition to the weight parameters, specifically, the ratio of the actual index to the maximum capacity index of the line may be used for dimension conversion.
In step S1014, a resource calculation model is created for the number of candidate network lines based on the weight parameters and the dimension parameters.
Further, referring to fig. 3, fig. 3 is a method for selecting a network line according to another embodiment of the present disclosure, which further includes step S1015 after step S1011 and before step S1012, and further divides step S1012 into step S1012a and step S1012b, and further divides step S1013 into step S1013a.
In step S1015, the current resource status of each index of each candidate network line, the maximum capability value of each index of each candidate network line, and the average resource status of each index of all candidate network lines are obtained.
Specifically, the current real-time performance data (average number of packets num, size of flow table, port forwarding rate r, and network forwarding times h required by each line) of each line are counted
Then, calculating the average resource condition of all the alternative lines according to the real-time performance data and the forwarding times of each line, wherein the average resource condition comprises the average forwarding times:
wherein
Representing the real-time packet number, flow table size, port forwarding rate and network forwarding times of the ith line, m representing m alternative network lines,
average packet number, flow table size, port forwarding rate and network forwarding times representing all alternative linesAnd (4) counting.
In step S1012a, respectively determining an adjustment factor for each index of each candidate network line based on the current resource situation of each index of each candidate network line and the average resource situation of each index of all candidate network lines; and the number of the first and second groups,
in step S1012b, a weight is respectively assigned to each index of each candidate network line based on the adjustment factor of each index of each candidate network line, so as to obtain a weight parameter of each index of each candidate network line.
Specifically, step S1012a is obtained according to the following formula:
step S1012b, the following formula is obtained:
in the formula (I), the compound is shown in the specification,
representing the weight of the jth index of the ith alternative network line;
the initial weight of the jth index of the ith alternative network line is represented and is a constant;
an adjustment factor representing the jth index of the ith alternative network line;
the current resource condition, avg, of the jth index of the ith alternative network line j Representing the average resource condition of j indexes of all lines;
in this embodiment, when the real-time condition of an index of a certain line is greater than the average value, it represents that the index has a relatively large resource for the line, and an influence factor on the index should be increased; when the real-time condition of a certain index of a certain line is smaller than the average value, the index represents that the relative resource of the certain index to the line is small, and the influence factor to the certain index is reduced; the adjustment factors of all indexes of each line are calculated according to the preset model through the resource condition of each line and the average resource condition of all the alternative lines, and the problems that the performance of the whole network line is affected and the like because some indexes of some lines run at full load and some indexes have large resources and are not distributed are solved through adjusting the adjustment factors in real time.
It should be noted that the initial weight
The weight before adjustment of the jth index representing the ith line is a default parameter, for example, the weight of the default initial four indexes is 0.25, and then the set initial weight parameter is continuously adjusted along with real-time data.
In step S1013a, dimension conversion is performed on each index of each candidate network line based on the current resource condition of each index of each candidate network line and the maximum capability value of each index of each candidate network line.
Specifically, step S1013a is obtained according to the following formula:
in the formula (I), the compound is shown in the specification,
dimension parameters of j index of the ith candidate network line,
represents the current resource situation of the jth index of the ith alternative network line,
and the maximum capacity value of the j index of the ith alternative network line is represented.
It can be understood that the maximum capability value of the jth index of the ith alternative network line, for example, the index of the number of network forwarding times
That is, the maximum number of forwarding times of all lines is the maximum capability index.
Further, step S101 is obtained according to the following formula:
in the formula, S i The resource score of the ith candidate network line is represented, n represents the index item number,
dimension parameters of j index of the ith candidate network line,
and the weight parameter represents the j index of the ith alternative network line.
In this embodiment, based on the weight and the dimension parameter of each index of each alternative network line, the obtained real-time resource calculation model calculates the sum of the data of each index of each alternative line and the product of the respective weights, to obtain the final resource score of each alternative network line, and then selects the candidate network line with the smallest score as the selection of the target line according to the obtained candidate network line, where the smallest score represents the smallest resource of the current line.
Based on the same technical concept, the embodiment of the present disclosure correspondingly provides a network line selection system, as shown in fig. 4, the network line selection system includes:
a model creation module 41 arranged to create a resource calculation model for a number of alternative network routes;
a calculating module 42 configured to calculate resource scores of the alternative network lines respectively based on the resource calculation model; and the number of the first and second groups,
a selection module 43 configured to select the candidate network line with the least resource score as the target network line based on the resource score of each candidate network line.
Based on the same technical concept, the embodiment of the present disclosure correspondingly provides a terminal device, as shown in fig. 5, the terminal device includes a memory 51 and a processor 52, a computer program is stored in the memory 52, and when the processor 51 runs the computer program stored in the memory 52, the processor 52 executes the network selection method.
Based on the same technical concept, embodiments of the present disclosure correspondingly provide a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the processor executes the network selection method.
It will be understood by those of ordinary skill in the art that all or some of the steps of the methods, systems, functional modules/units in the devices disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof. In a hardware implementation, the division between functional modules/units mentioned in the above description does not necessarily correspond to the division of physical components; for example, one physical component may have multiple functions, or one function or step may be performed by several physical components in cooperation. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). The term computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data, as is well known to those of ordinary skill in the art. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can accessed by a computer. In addition, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media as known to those skilled in the art.
Finally, it should be noted that: the above embodiments are only used for illustrating the technical solutions of the present disclosure, and not for limiting the same; although the present disclosure has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art will understand that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present disclosure.
Claims (8)
1. A network line selection method, comprising:
creating a resource calculation model for a plurality of alternative network lines;
respectively calculating the resource score of each alternative network line based on the resource calculation model; and the number of the first and second groups,
selecting the alternative network line with the least resource score as a target network line based on the resource score of each alternative network line;
the creating of the resource calculation model for the plurality of alternative network lines comprises:
determining a plurality of indexes for calculating resource scores of the alternative network lines;
respectively obtaining the current resource condition of each index of each alternative network line, the maximum capacity value of each index of each alternative network line and the average resource condition of each index of all alternative network lines;
respectively determining an adjusting factor of each index of each alternative network line based on the current resource condition of each index of each alternative network line and the average resource condition of each index of all alternative network lines;
respectively distributing weight to each index of each alternative network line based on the adjustment factor of each index of each alternative network line to obtain the weight parameter of each index of each alternative network line;
performing dimension conversion on each index of each alternative network line respectively based on the current resource condition of each index of each alternative network line and the maximum capacity value of each index of each alternative network line to obtain a dimension parameter of each index of each alternative network line; and the number of the first and second groups,
and creating a resource calculation model for the plurality of alternative network lines based on the weight parameters and the dimension parameters.
2. The method of claim 1, further comprising, prior to creating the resource computation model for a number of alternative network wires:
screening a plurality of network lines which accord with preset conditions as alternative network lines according to current flow information after a data center enters a peak period;
the traffic information includes a source IP address, a source port, a destination IP address, and a destination port.
3. The method according to claim 1, wherein the adjustment factor of each index of each candidate network line is determined based on the current resource situation of each index of each candidate network line and the average resource situation of each index of all candidate network lines, and is obtained according to the following formula:
the adjusting factor based on each index of each alternative network line distributes weight to each index of each alternative network line respectively to obtain a weight parameter of each index of each alternative network line, and the weight parameter is obtained according to the following formula:
in the formula (I), the compound is shown in the specification,
the weight parameter represents the jth index of the ith alternative network line;
the initial weight parameter which represents the jth index of the ith alternative network line is a constant;
an adjustment factor representing the jth index of the ith alternative network line;
the current resource condition, avg, of the jth index of the ith alternative network line j And the average resource situation of j indexes of all the alternative lines is shown.
4. The method according to claim 1, wherein the dimension conversion is performed on each index of each candidate network line, and is obtained according to the following formula:
in the formula (I), the compound is shown in the specification,
dimension parameters of j index of the ith candidate network line,
represents the current resource situation of the jth index of the ith alternative network line,
and the maximum capacity value of the j index of the ith alternative network line is represented.
5. The method of claim 1, wherein the creating a resource calculation model for the number of candidate network lines based on the weight parameters and the dimension parameters is performed according to the following formula:
in the formula, S i The resource score of the ith candidate network line is represented, n represents the index item number,
dimension parameters of j index of the ith candidate network line,
and the weight parameter represents the j index of the ith alternative network line.
6. A network routing system, comprising:
a model creation module configured to create a resource calculation model for a number of alternative network lines;
a calculation module configured to calculate resource scores of the alternative network lines, respectively, based on the resource calculation model; and the number of the first and second groups,
a selection module configured to select, as a target network line, an alternative network line having a smallest resource score based on the resource score of each alternative network line;
wherein the model creation module is specifically configured to:
determining a plurality of indexes for calculating resource scores of the alternative network lines;
respectively obtaining the current resource condition of each index of each alternative network line, the maximum capacity value of each index of each alternative network line and the average resource condition of each index of all alternative network lines;
respectively determining an adjusting factor of each index of each alternative network line based on the current resource condition of each index of each alternative network line and the average resource condition of each index of all alternative network lines;
respectively distributing weight to each index of each alternative network line based on the adjustment factor of each index of each alternative network line to obtain the weight parameter of each index of each alternative network line;
performing dimension conversion on each index of each alternative network line respectively based on the current resource condition of each index of each alternative network line and the maximum capacity value of each index of each alternative network line to obtain a dimension parameter of each index of each alternative network line; and (c) a second step of,
and creating a resource calculation model for the plurality of alternative network lines based on the weight parameters and the dimension parameters.
7. A terminal device characterized by comprising a memory in which a computer program is stored and a processor which executes the network line selection method according to any one of claims 1 to 5 when the processor runs the computer program stored in the memory.
8. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out a network line selection method according to any one of claims 1 to 5.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102045261A (en) * | 2011-01-04 | 2011-05-04 | 南京邮电大学 | Routing method based on bionic process in cognitive network |
| CN105429894A (en) * | 2015-11-30 | 2016-03-23 | 国网冀北电力有限公司信息通信分公司 | Service route selection method and device in electric power communication network |
| CN108206781A (en) * | 2016-12-16 | 2018-06-26 | 华为技术有限公司 | The method and apparatus for selecting forward-path |
| CN109981765A (en) * | 2019-03-18 | 2019-07-05 | 北京百度网讯科技有限公司 | Method and apparatus for determining the access path of content distributing network |
| CN111654873A (en) * | 2019-09-27 | 2020-09-11 | 西北大学 | Mobile CDN link selection energy consumption optimization method based on global utility cache strategy |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102065544B (en) * | 2009-11-17 | 2015-02-25 | 索尼株式会社 | Resource management method and system |
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Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102045261A (en) * | 2011-01-04 | 2011-05-04 | 南京邮电大学 | Routing method based on bionic process in cognitive network |
| CN105429894A (en) * | 2015-11-30 | 2016-03-23 | 国网冀北电力有限公司信息通信分公司 | Service route selection method and device in electric power communication network |
| CN108206781A (en) * | 2016-12-16 | 2018-06-26 | 华为技术有限公司 | The method and apparatus for selecting forward-path |
| CN109981765A (en) * | 2019-03-18 | 2019-07-05 | 北京百度网讯科技有限公司 | Method and apparatus for determining the access path of content distributing network |
| CN111654873A (en) * | 2019-09-27 | 2020-09-11 | 西北大学 | Mobile CDN link selection energy consumption optimization method based on global utility cache strategy |
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