Cross-region C / S architecture system network configuration optimization method, device and medium

Abstract

The embodiment of the present invention discloses a cross-regional C / S architecture system network configuration optimization method, device and medium, the method comprising: generating multiple test recipes according to preset test key variables, the test key variables comprising: server access number range parameter, bandwidth upper limit range parameter and delay range parameter; using the multiple test recipes to perform simulation tests to obtain test results; generating a comparison list according to the test recipes, test results and the costs corresponding to the test recipes; sorting the cost-generated comparison list according to the costs; and optimizing and designing the server network configuration service plan based on the sorting results. The network environment can be optimized without determining the bottleneck point of the network environment, and compared with the bottleneck point improvement method, it can achieve a significant optimization of the network environment at a lower cost.

Description

Technical Field

[0001] The present invention relates to the technical field of network configuration optimization, and in particular to a method, device and medium for optimizing network configuration of a cross-regional C / S architecture system. Background Art

[0002] With the widespread application of cloud computing and distributed systems and the extensive development of cross-domain offices, cross-regional client / server architecture has become a common system design choice for office systems to provide high availability, flexible resource allocation, and improve the service experience of geographically dispersed users.

[0003] However, the cross-regional network environment is complex and changeable. The network delay between servers and between servers and clients fluctuates greatly and is often affected by multiple factors, such as physical distance, the quality of network facilities, and network traffic conditions. These factors lead to deviations between service performance and reliability and expectations in actual operations, especially during peak network load periods. In the prior art, bottlenecks can be determined through ideal performance and actual network test results, and the bottlenecks can be improved to optimize the network environment and improve the network environment.

[0004] In the process of implementing the present invention, the inventors found the following technical problems: Although the existing technology can optimize the network environment to a certain extent by improving the bottleneck points, there may be multiple reasons for the deterioration of the network environment and they affect each other, making it difficult to determine the specific improvement elements. Although simply improving the bottleneck points can optimize the network environment to a certain extent, the degree of optimization is relatively limited. Summary of the invention

[0005] The embodiments of the present invention provide a method, device and medium for optimizing network configuration of a cross-region C / S architecture system, so as to solve the technical problem in the prior art that the optimization effect of the network of a cross-region C / S architecture system is limited.

[0006] In a first aspect, an embodiment of the present invention provides a method for optimizing network configuration of a cross-regional C / S architecture system, including:

[0007] Generate multiple test recipes according to preset test key variables, wherein the test key variables include: server access quantity range parameter, bandwidth upper limit range parameter and delay range parameter;

[0008] Performing simulation tests using the multiple test recipes to obtain test results;

[0009] Generate a comparison list based on test recipes, test results, and costs corresponding to the test recipes;

[0010] Sort the cost generation comparison list by cost;

[0011] Optimize and design server network configuration service solutions based on the sorting results.

[0012] In a second aspect, an embodiment of the present invention further provides a cross-region C / S architecture system network configuration optimization device, including:

[0013] A generating module, used to generate a plurality of test recipes according to preset key test variables, wherein the key test variables include: a server access quantity range parameter, a bandwidth upper limit range parameter and a delay range parameter;

[0014] A test module, used to perform simulation tests using the multiple test recipes to obtain test results;

[0015] A list generation module, used for generating a comparison list according to the test formula, the test results and the cost corresponding to the test formula;

[0016] A sorting module, used to sort the cost generation comparison list according to cost;

[0017] The optimization module is used to optimize the design of server network configuration service solutions based on the sorting results.

[0018] In a third aspect, an embodiment of the present invention further provides a storage medium comprising computer executable instructions, which, when executed by a computer processor, are used to execute the cross-regional C / S architecture system network configuration optimization method provided in the above embodiment.

[0019] The cross-regional C / S architecture system network configuration optimization method, device and storage medium provided by the embodiment of the present invention generate multiple test recipes according to preset test key variables, and the test key variables include: server access number range parameter, bandwidth upper limit range parameter and delay range parameter; use the multiple test recipes to perform simulation tests to obtain test results; generate a comparison list according to the test recipes, test results and the costs corresponding to the test recipes; sort the cost-generated comparison list according to the cost; and optimize the server network configuration service plan based on the sorting results. Multiple configuration plans can be generated according to the load requirement range of the park server, and simulation tests can be performed based on each configuration plan. According to the multiple results of the simulation test, a configuration plan that meets the requirements of the network environment can be selected, and the most suitable optimization plan can be selected for optimization according to the cost of each configuration plan. Using the above method, the network environment can be optimized without determining the bottleneck point of the network environment, and compared with the bottleneck point improvement method, it can achieve a significant optimization of the network environment at a lower cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0021] Figure 1 It is a flowchart of a cross-region C / S architecture system network configuration optimization method provided by the first embodiment of the present invention;

[0022] Figure 2 It is a flowchart of a cross-region C / S architecture system network configuration optimization method provided by Embodiment 2 of the present invention;

[0023] Figure 3 It is a structural diagram of a cross-regional C / S architecture system network configuration optimization device provided in Embodiment 3 of the present invention. DETAILED DESCRIPTION

[0024] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only parts related to the present invention, rather than all structures, are shown in the accompanying drawings.

[0025] Embodiment 1

[0026] Figure 1 1 is a flowchart of a method for optimizing network configuration of a cross-regional C / S architecture system provided in Embodiment 1 of the present invention. This embodiment can optimize the network configuration of a cross-regional C / S architecture system. The method can be executed by a device for optimizing network configuration of a cross-regional C / S architecture system, and specifically includes the following steps:

[0027] Step 110, generating multiple test recipes according to preset test key variables, wherein the test key variables include: server access quantity range parameter, bandwidth upper limit range parameter and delay range parameter.

[0028] In this embodiment, the cross-regional C / S architecture system may be a C / S architecture system for multiple parks within an enterprise. Users in each park may use a client to access servers in other parks at a certain physical distance via a wide area network to obtain corresponding services.

[0029] Optionally, a park can be selected and a test formula can be set based on the park. The test formula can be generated using key test variables, which include: server access number range parameter, bandwidth upper limit range parameter and delay range parameter. Exemplarily, the server access number range parameter can be based on the concurrent access number range generated by the number of users who may use the server in other parks; the bandwidth upper limit range parameter can be determined based on the bandwidth range that may be provided by the network operator; the delay range parameter can be based on the network delay parameter that can be accepted when the server provides services normally, to determine the network delay range. Optionally, when it is determined that the application scope of the server is for internal use, the local and remote access volume is determined according to the service of the server; and the bandwidth upper limit range parameter of each park is set based on the remote access volume. That is, the number of accesses to the server in each park is determined by the reasonable distribution of the number of users in the park, and this method can also reduce the overall operating cost of the park C / S architecture system.

[0030] Optionally, multiple test recipes may be generated by traversing and combining the above key test variables.

[0031] Step 120, using the multiple test recipes to perform simulation tests to obtain test results.

[0032] Exemplarily, the multiple test recipes obtained according to the above steps can be tested using the constructed simulation test platform, and corresponding test results can be obtained respectively.

[0033] Step 130 , generating a comparison list according to the test recipes, the test results, and the costs corresponding to the test recipes.

[0034] Exemplarily, each of the test recipes corresponds to a server configuration and a network configuration, and the cost required for the configuration can be calculated using the server configuration and the network configuration. A cost generation ratio list is generated based on the cost, recipe and test results.

[0035] Step 140 , sorting the cost generation comparison list according to cost.

[0036] Exemplarily, the cost generation comparison list may be sorted in order from low to high according to the cost.

[0037] Step 150: Optimize and design a server network configuration service solution based on the sorting results.

[0038] Exemplarily, it may include: obtaining the lowest-cost campus server configuration, campus bandwidth purchase service, and campus network device configuration that meet the test result range in the sorting results; using the campus server configuration, campus bandwidth purchase service, and campus network device configuration as a design server network configuration service plan. The sorting results may be used to determine the results that can meet the access requirements of the campus server. Usually, there are multiple results that meet this requirement. The lowest-cost test formula may be selected from them, and the campus network device configuration may be optimized based on the campus server configuration, campus bandwidth purchase service, and campus network device configuration corresponding to the test formula as an optimization plan.

[0039] This embodiment generates multiple test recipes according to preset key test variables, and the key test variables include: server access number range parameter, bandwidth upper limit range parameter and delay range parameter; uses the multiple test recipes to perform simulation tests to obtain test results; generates a comparison list according to the test recipes, test results and the costs corresponding to the test recipes; sorts the cost-generated comparison list according to the costs; and optimizes and designs the server network configuration service plan based on the sorting results. Multiple configuration plans can be generated according to the load requirement range of the park server, and simulation tests can be performed based on each configuration plan. According to the multiple results of the simulation tests, a configuration plan that meets the requirements of the network environment can be selected, and the most suitable optimization plan can be selected for optimization according to the cost of each configuration plan. Using the above method, the network environment can be optimized without determining the bottleneck point of the network environment, and compared with the bottleneck point improvement method, it can achieve a significant optimization of the network environment at a lower cost.

[0040] In a preferred implementation of this embodiment, the method may further include the following steps: when the cost of the design server network configuration service solution exceeds a cost threshold, the off-site access volume of the park is adjusted, and multiple test recipe steps are generated according to preset test key variables until the cost is lower than the cost threshold or the preset number of generation times. When the cost of the optimized solution obtained by the above steps still cannot meet the requirements, the purpose of reducing the network configuration cost can be achieved by reasonably configuring the park users.

[0041] Embodiment 2

[0042] Figure 2This is a flow chart of the cross-regional C / S architecture system network configuration optimization method provided by the second embodiment of the present invention. This embodiment is optimized based on the above embodiment, and the method can also add the following steps: obtain the container types of the server's external services and the long-term changes of each container type; establish a container type quantity change distribution model based on the long-term changes; determine the container quantity range of each service type based on the container type quantity change distribution model; determine the access quantity range parameter based on the container quantity range. Monitor the actual network delay between each park and obtain data through ping test; count the network delay data and establish a network delay distribution model based on the statistical results; use the distribution model to simulate the delay situation in the real network environment; determine the delay range parameter based on the delay situation.

[0043] See also Figure 2 The cross-regional C / S architecture system network configuration optimization method includes:

[0044] Step 210: Obtain the container types that the server serves externally and the long-term changes of each container type; and establish a container type quantity change distribution model based on the long-term changes.

[0045] At present, servers provide users with various services through containers. Containers have the advantages of fast creation and startup, low resource usage, small package size, simplified deployment, improved productivity, portable operating environment, scalability, independent upgrade, lightweight, high performance, portability, environment standardization and version control. Each container can provide users with a variety of microservices. Container technology can flexibly deploy various services.

[0046] In this embodiment, the possible number of concurrent accesses can be determined for each microservice provided by various containers. Compared with the method of simply estimating the number of users, the evaluation is more accurate. Exemplarily, the long-term changes of container types and each container type in the server can be used; a distribution model for changes in the number of container types is established based on the long-term changes. This model is used to reflect the number of container types and the changes in the number of each container of each type. Exemplarily, due to the low number of visits to a certain microservice, the number of containers may gradually decrease. Correspondingly, the number of containers of some types may increase. Through long-term changes, a distribution model for changes in the number of container types can be established.

[0047] Step 220: determine the container quantity range of each service type according to the container type quantity change distribution model; and determine the access quantity range parameter according to the container quantity range.

[0048] By using the container type quantity change distribution model, we can not only remove the noise points in extreme cases, but also estimate the quantity of each container. Then, we can estimate the number of accesses at different times through information such as the number of containers, container types, and the number of concurrent containers. Based on the number of accesses, we can determine the range parameters of the number of accesses. This method can more accurately determine the range parameters of the number of accesses, thereby reducing the number of recipes generated in the later stage and preventing meaningless test recipes from wasting more network resources and computing power.

[0049] Step 230, monitor the actual network delay between the parks, obtain data through ping test; collect statistics on the network delay data, and establish a distribution model of the network delay based on the statistical results.

[0050] For example, since network delay is mainly determined by transmission distance and intermediate switching paths, the network delay parameters need to be determined in combination with the actual conditions between parks. In this embodiment, ping is used to obtain delay data, and a corresponding network delay distribution model is established in combination with long-term statistics.

[0051] Step 240, using the distribution model to simulate the delay situation in a real network environment; and determining a delay range parameter according to the delay situation.

[0052] For example, the distribution model can not only remove noise points in special cases, but also obtain a data range of uniformly distributed network delays, and setting delay range parameters using the data range can be more accurate. Reduce the number of recipes.

[0053] Step 250: Generate multiple test recipes according to preset test key variables, wherein the test key variables include: server access quantity range parameter, bandwidth upper limit range parameter and delay range parameter.

[0054] Step 260 , using the multiple test recipes to perform simulation tests to obtain test results, and generating a comparison list according to the test recipes, the test results, and the costs corresponding to the test recipes.

[0055] Step 270, sorting the cost generation comparison list according to the cost, and optimizing and designing the server network configuration service solution based on the sorting result.

[0056] This embodiment adds the following steps: obtaining the container types of the server's external services and the long-term changes of each container type; establishing a distribution model for changes in the number of container types based on the long-term changes; determining the range of container quantities for each service type based on the distribution model for changes in the number of container types; and determining access quantity range parameters based on the container quantity range. Monitor the actual network delay between the parks and obtain data through ping tests; collect statistics on network delay data and establish a distribution model for network delay based on the statistical results; use the distribution model to simulate delay conditions in a real network environment; and determine delay range parameters based on the delay conditions. Using the above method, key test variables can be predicted more accurately, preventing the generation of a large number of meaningless test recipes, and effectively reducing the workload of simulation testing.

[0057] In a preferred implementation of this embodiment, the test results include: response time, throughput, error rate, resource utilization and service interruption; accordingly, the method can also add the following steps: compare the collected test results with the preset performance benchmark; when the comparison result exceeds the preset threshold, adjust the range of the key test variables. In this way, it can be prevented that in some special cases, for example, when the local access volume is much larger than the access volume of other parks, the amount of bandwidth far exceeds the demand, resulting in resource waste.

[0058] Embodiment 3

[0059] Figure 3 This is a schematic diagram of the structure of the cross-regional C / S architecture system network configuration optimization device provided by the fourth embodiment of the present invention, see Figure 3 The cross-regional C / S architecture system network configuration optimization device includes:

[0060] A generating module 310, for generating a plurality of test recipes according to preset key test variables, wherein the key test variables include: a server access quantity range parameter, a bandwidth upper limit range parameter, and a delay range parameter;

[0061] A test module 320 is used to perform simulation tests using the multiple test recipes to obtain test results;

[0062] A list generation module 330, for generating a comparison list according to the test recipe, the test results and the cost corresponding to the test recipe;

[0063] A sorting module 340, for sorting the cost generation comparison list according to cost;

[0064] The optimization module 350 is used to optimize and design the server network configuration service solution based on the sorting result.

[0065] The cross-regional C / S architecture system network configuration optimization device provided in this embodiment generates multiple test recipes according to preset test key variables, and the test key variables include: server access number range parameter, bandwidth upper limit range parameter and delay range parameter; uses the multiple test recipes to perform simulation tests to obtain test results; generates a comparison list according to the test recipes, test results and the costs corresponding to the test recipes; sorts the cost-generated comparison list according to the cost; and optimizes and designs the server network configuration service plan based on the sorting results. According to the load requirement range of the park server, multiple configuration plans can be generated, and simulation tests can be performed based on each configuration plan. According to the multiple results of the simulation test, a configuration plan that meets the requirements of the network environment can be selected, and the most suitable optimization plan can be selected for optimization according to the cost of each configuration plan. Using the above method, the network environment can be optimized without determining the bottleneck point of the network environment, and compared with the bottleneck point improvement method, it can achieve a significant optimization of the network environment at a lower cost.

[0066] Based on the above embodiments, the key test variables also include: the number of parks,

[0067] Accordingly, the generating module includes:

[0068] A determination unit, configured to determine the local and remote access amounts according to the service of the server when determining that the application scope of the server is internal use;

[0069] The setting unit is used to set the bandwidth upper limit range parameters of each park based on the remote access volume.

[0070] Based on the above embodiments, the optimization module includes:

[0071] An acquisition unit, used to acquire the lowest-cost campus server configuration, campus bandwidth purchase service and campus network device configuration that conforms to the test result range in the sorting results;

[0072] As a unit, it is used to configure the park server, purchase bandwidth services in the park and configure the park network equipment as a design server network configuration service plan.

[0073] Based on the above embodiments, the device further includes:

[0074] The return module is used to adjust the off-site access volume of the campus when the cost of the designed server network configuration service plan exceeds the cost threshold, and return to generate multiple test recipe steps based on preset test key variables until it is lower than the cost threshold or the preset number of generations.

[0075] Based on the above embodiments, the device further includes:

[0076] The adjustment module is used to adjust the maximum delay time of the CPU N from the energy-saving state to the performance state.

[0077] Based on the above embodiments, the device further includes:

[0078] A modification module is used to change the dynamic frequency adjustment mode of CPU N to the performance mode.

[0079] Based on the above embodiments, the device further includes:

[0080] The first change acquisition module is used to acquire the container types of external services provided by the server and the long-term changes of each container type;

[0081] A first establishing module is used to establish a container type quantity change distribution model according to the long-term change;

[0082] A first range determination module is used to determine the range of the number of containers for each service type according to a container type quantity change distribution model;

[0083] The first parameter determination module is used to determine an access quantity range parameter according to the container quantity range.

[0084] Based on the above embodiments, the device further includes:

[0085] The monitoring module is used to monitor the actual network delay between the parks and obtain data through ping tests;

[0086] The second establishment module is used to collect statistics on network delay data and establish a distribution model of network delay based on the statistical results;

[0087] A simulation module, used to simulate the delay situation in a real network environment using the distribution model;

[0088] The second parameter determination module is used to determine the delay range parameter according to the delay situation.

[0089] Based on the above embodiments, the test results include: response time, throughput, error rate, resource utilization and service interruption;

[0090] Accordingly, the device further comprises:

[0091] A comparison module, used to compare the collected test results with the preset performance benchmark;

[0092] The adjustment module is used to adjust the range of the key test variable when the comparison result exceeds a preset threshold.

[0093] The cross-regional C / S architecture system network configuration optimization device provided in the embodiment of the present invention can execute the cross-regional C / S architecture system network configuration optimization method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0094] Embodiment 4

[0095] Embodiment 4 of the present invention further provides a storage medium comprising computer executable instructions, which, when executed by a computer processor, are used to execute the cross-regional C / S architecture system network configuration optimization method as described in any of the above embodiments.

[0096] The computer storage medium of the embodiment of the present invention may adopt any combination of one or more computer-readable media. The computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination thereof. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, device or device.

[0097] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0098] Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0099] Computer program code for performing the operation of the present invention may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or device. 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 may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0100] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A cross-regional C / S architecture system network configuration optimization method, characterized in that: include: Generate multiple test recipes according to preset test key variables, wherein the test key variables include: server access quantity range parameter, bandwidth upper limit range parameter and delay range parameter; Performing simulation tests using the multiple test recipes to obtain test results; Generate a comparison list based on test recipes, test results, and costs corresponding to the test recipes; Sort the comparison list by cost; Optimize and design server network configuration service solutions based on the sorting results; The server network configuration service solution is optimized and designed based on the sorting results, including: Obtaining the lowest-cost campus server configuration, campus-purchased bandwidth service, and campus network device configuration that are within the test result range from the sorting results; The park server configuration, the park bandwidth purchase service and the park network equipment configuration are used as the design server network configuration service plan.

2. The method according to claim 1, characterized in that The key variables of the test also include: the number of parks, Accordingly, the multiple test recipes are generated according to the preset key test variables, including: When it is determined that the application scope of the server is internal use, the local and remote access volumes are determined according to the service of the server; The bandwidth upper limit range parameters of each park are set based on the remote access volume.

3. The method according to claim 2, characterized in that The method further comprises: When the cost of the designed server network configuration service plan exceeds the cost threshold, the off-site access volume of the campus is adjusted, and multiple test recipe steps are generated according to preset key test variables until it is lower than the cost threshold or the preset number of generations.

4. The method according to claim 2, characterized in that: The method further comprises: Obtain the container types that the server provides external services and the long-term changes of each container type; Establishing a container type quantity change distribution model based on the long-term changes; Determine the range of container quantity for each service type based on the container type quantity change distribution model; An access quantity range parameter is determined according to the container quantity range.

5. The method according to claim 2, characterized in that: The method further comprises: Monitor the actual network latency between campuses and obtain data through ping tests; Collect statistics on network delay data and establish a network delay distribution model based on the statistical results; Using the distribution model to simulate the delay situation in a real network environment; A delay range parameter is determined according to the delay condition.

6. The method according to claim 3, characterized in that: The test results include: response time, throughput, error rate, resource utilization and service interruption; Accordingly, the method further comprises: comparing the collected test results with a preset performance benchmark; When the comparison result exceeds a preset threshold, the range of the key test variable is adjusted.

7. A cross-regional C / S architecture system network configuration optimization device, characterized in that: include: A generating module, used to generate a plurality of test recipes according to preset key test variables, wherein the key test variables include: a server access quantity range parameter, a bandwidth upper limit range parameter and a delay range parameter; A test module, used to perform simulation tests using the multiple test recipes to obtain test results; A list generation module, used for generating a comparison list according to the test formula, the test results and the cost corresponding to the test formula; A sorting module, used to sort the comparison list by cost; An optimization module, used to optimize and design server network configuration service solutions based on the sorting results; The optimization module includes: An acquisition unit, used to acquire the lowest-cost campus server configuration, campus bandwidth purchase service and campus network device configuration that conforms to the test result range in the sorting results; As a unit, it is used to configure the park server, purchase bandwidth services in the park and configure the park network equipment as a design server network configuration service plan.

8. A storage medium containing computer executable instructions, characterized in that: The computer executable instructions are used to execute the cross-regional C / S architecture system network configuration optimization method as described in any one of claims 1-6 when executed by a computer processor.

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