Computing power optimization method and system for cloud computing data center transmission

Abstract

The invention discloses a computing power optimization method and system for cloud computing data center transmission. The system comprises a network parameter integration module and a computing resource computing power optimization module. The network parameter integration module is arranged in a cloud computing data center to monitor tasks, and prestores and sets reference flow loads of network topology structures in different unit time, transmission network bandwidths, time delays and packet loss rates. Network topology structure flow loads, transmission network bandwidths, time delays and packet loss rates in different unit time are collected through a flow analyzer module, and the network fault-tolerant rate is obtained by comparing the network topology structure flow loads, transmission network bandwidths, time delays and packet loss rates in different unit time with a reference flow load, transmission network bandwidths, time delays and packet loss rates. And a calculation and analysis result is obtained by comparing the data throughput with the network fault-tolerant rate. According to the method, the problems that the bandwidth, time delay and packet loss probability detection method of the transmission network of the existing network topology structure in different unit time is complicated, and a computing power system cannot be controlled are solved.

Description

Technical Field

[0001] The present invention relates to the field of cloud computing data center management, and in particular to a computing power optimization method and system for cloud computing data center transmission. Background Art

[0002] With the rapid development of cloud computing technology, data centers, as core infrastructures that carry massive computing and storage tasks, play a vital role in the overall computing power optimization through their transmission network performance. In cloud computing data centers, a large number of tasks require data transmission between different nodes. Key performance parameters such as bandwidth, latency, and packet loss rate of the transmission network directly affect the task completion efficiency and service quality. The network topology of data centers is complex and diverse. From the traditional tree architecture to the modern fat tree, ring structure, and the emerging software-defined network (SDN), efficient computing power optimization methods are needed to achieve dynamic management and reasonable allocation of resources. However, these optimization tasks require accurate grasp of the real-time status of the transmission network. Therefore, accurate monitoring of network performance parameters has become a key prerequisite for improving the efficiency of computing power optimization.

[0003] At present, the detection technology of transmission network performance in cloud computing data centers mostly relies on built-in functions and monitoring tools of devices. For example, traffic data is collected from switches, routers and other devices through the SNMP protocol, or latency and packet loss rate information is obtained with the help of tools such as Ping and Traceroute. In addition, advanced network performance management tools such as NetFlow and sFlow are also widely used for network status monitoring in data centers. However, these methods usually require a lot of hardware support, and the data collection and processing process involves the coordination of multiple protocols and devices. Especially in the face of dynamically changing network topologies, the existing technology has certain limitations in monitoring network performance parameters in different unit times, and cannot quickly and accurately adapt to complex data flow changes.

[0004] Although the above methods provide basic support for the transmission network performance detection of data centers, they still have the following shortcomings: First, the detection complexity of existing methods is high and they are highly dependent on network equipment and protocols, resulting in high deployment and maintenance costs in heterogeneous network environments. Secondly, in a multi-level topology, the dynamic changes of network performance parameters are relatively fast. Traditional sampling methods are difficult to capture the precise fluctuations of transmission network bandwidth, latency, and packet loss rate in real time, which increases the difficulty of monitoring. In addition, most existing monitoring tools run independently, with poor data interoperability, and it is not easy to achieve comprehensive analysis of network performance from a global perspective. These problems are further magnified in the context of the continuous expansion of the scale of cloud computing data centers. There is an urgent need for a solution with higher detection accuracy, lower deployment cost, and stronger real-time performance to support efficient computing power optimization methods. Summary of the invention

[0005] The purpose of the present invention is to provide a computing power optimization method and system for cloud computing data center transmission, aiming to solve the problems of complex detection, difficult monitoring, and inability to system management in the current methods for detecting network bandwidth, delay, and packet loss rate of network topology structures with different unit time units. In order to achieve the above object, the present invention adopts the following technical solutions: A first aspect of the present invention provides a computing power optimization system for cloud computing data center transmission, including a network parameter integration module and a computing resource computing power optimization module; The network parameter integration module is set in the cloud computing data center monitoring task, and the network parameter integration module pre-stores the benchmark traffic load and transmission network bandwidth, delay, and packet loss rate of network topology structures at different unit times, collects the traffic load and transmission network bandwidth, delay, and packet loss rate of network topology structures at different unit times through the traffic analyzer module, compares the traffic load and transmission network bandwidth, delay, and packet loss rate of network topology structures at different unit times with the benchmark traffic load and transmission network bandwidth, delay, and packet loss rate to obtain the network fault tolerance rate, obtains the calculation and analysis results by comparing the data throughput and the network fault tolerance rate, and calculates the service response time for the transmission network bandwidth, delay, and packet loss rate of network topology structures at different unit times; wherein, the transmission network bandwidth, delay, and packet loss rate of network topology structures at different unit times include the calculation and analysis results, the benchmark traffic load and transmission network bandwidth, delay, packet loss rate, and network fault tolerance rate; The computing resource power optimization module obtains and displays the network bandwidth, latency, and packet loss rate of the network topology structure transmission at different unit times, and distributes and executes tasks by real-time monitoring of the resource utilization of computing nodes, combined with intelligent scheduling and load balancing strategies. At the same time, by balancing resource utilization and energy consumption optimization, it dynamically adjusts computing resources and task migration technology to reduce energy consumption.

[0006] Preferably, the network parameter integration module includes a traffic analyzer module monitoring unit, a CPU operating frequency limiting unit and a task queue management unit. The traffic analyzer module monitoring unit obtains the network topology traffic load and transmission network bandwidth, delay, and packet loss rate of different unit times through the CPU system, and transmits them to the CPU operating frequency limiting unit. The CPU operating frequency limiting unit receives the network topology traffic load and transmission network bandwidth, delay, and packet loss rate of different unit times and compares them with the pre-stored benchmark traffic load and transmission network bandwidth, delay, and packet loss rate, calculates the network fault tolerance rate between the two, and compares the network fault tolerance rate with the data throughput. When the network fault tolerance rate is greater than the data throughput, the calculation and analysis results are obtained that the network topology structures of different unit times are subject to the transmission network bandwidth, delay, and packet loss rate of the network topology structures of different unit times. The task queue management unit receives the network fault tolerance rate and the calculation and analysis results issued by the server control unit, and calculates the service response time for the received network topology transmission network bandwidth, delay, and packet loss rate of the network topology structures of different unit times.

[0007] Preferably, the traffic analyzer module monitoring unit includes a CPU frequency monitoring module, which operates under the control of the CPU operating frequency limiting unit. The CPU frequency monitoring module reduces the impact of abnormal transmission network bandwidth, delay, and packet loss rate of the network topology structure in different unit times on the traffic analyzer module monitoring.

[0008] Preferably, the task queue management unit is a CPU cache size transmission unit, which transmits calculation and analysis results, network fault tolerance and benchmark traffic load, and transmission network bandwidth, latency, and packet loss rate to the CPU system, and the computing resource computing power optimization module receives data through the CPU system.

[0009] Preferably, it also includes: a thread number management module, the computing resource computing power optimization module analyzes the obtained calculation and analysis results, network fault tolerance and benchmark traffic load, and transmission network bandwidth, delay, and packet loss rate, generates transmission network bandwidth, delay, and packet loss rate status data of network topology structures at different unit times and transmits them to the specified thread number management module; any thread number management module transmits a request to the computing resource computing power optimization module to obtain the transmission network bandwidth, delay, and packet loss rate of network topology structures at different unit times for cloud computing data center monitoring tasks.

[0010] Preferably, it also includes: a module for monitoring the bandwidth, delay and packet loss rate of the network topology structure transmission network with different unit time. The module for monitoring the bandwidth, delay and packet loss rate of the network topology structure transmission network with different unit time receives instructions transmitted by the server to adjust the bandwidth, delay and packet loss rate of the network topology structure transmission network with different unit time of the current task.

[0011] A second aspect of the present invention is to provide a computing power optimization method for cloud computing data center transmission using the above system, comprising the following steps: S100, setting a network parameter integration module in all cloud computing data center monitoring tasks, pre-storing the benchmark traffic load of network topology structures at different unit times and the transmission network bandwidth, delay, and packet loss rate in the network parameter integration module; S200, the network parameter integration module collects the network topology traffic load and transmission network bandwidth, delay, and packet loss rate of different unit time through the traffic analyzer module, and compares the network topology traffic load and transmission network bandwidth, delay, and packet loss rate of different unit time with the benchmark traffic load and transmission network bandwidth, delay, and packet loss rate to obtain the network fault tolerance rate; S300, the network parameter integration module compares the data throughput and the network fault tolerance rate to obtain calculation and analysis results, and calculates the service response time for the transmission network bandwidth, delay, and packet loss rate of the network topology structure with different unit time, wherein the transmission network bandwidth, delay, and packet loss rate of the network topology structure with different unit time include calculation and analysis results, benchmark traffic load, and transmission network bandwidth, delay, packet loss rate, and network fault tolerance rate; S400, computing resource computing power optimization module obtains and displays the network bandwidth, delay, and packet loss rate of the network topology structure transmission in different unit time, and distributes and executes tasks by real-time monitoring of the resource utilization of computing nodes, combined with intelligent scheduling and load balancing strategies. At the same time, through the balance of resource utilization and energy consumption optimization, it dynamically adjusts computing resources and task migration technology to reduce energy consumption; S500, the computing resource computing power optimization module obtains the transmission network bandwidth, delay and packet loss rate of network topology structures with different unit times, generates the transmission network bandwidth, delay and packet loss rate status data of network topology structures with different unit times according to the transmission network bandwidth, delay and packet loss rate of network topology structures with different unit times, and determines the different unit time network topologies with different unit time network topology structure transmission network bandwidth, delay and packet loss rate tasks through the benchmark traffic load and transmission network bandwidth, delay and packet loss rate, and transmits the transmission network bandwidth, delay and packet loss rate status data of network topology structures with different unit times to the thread number management module that manages the transmission network bandwidth, delay and packet loss rate tasks of network topology structures with different unit times.

[0012] Preferably, it also includes a step of adjusting the traffic load of the network topology structure at different unit times, and the step of adjusting the traffic load of the network topology structure at different unit times is that the computing resource computing power optimization module transmits the CPU frequency monitoring instruction to the network parameter integration module, and the network parameter integration module adjusts the network bandwidth, delay, and packet loss rate fluctuation range of the network topology structure transmission of the CPU frequency monitoring module at different unit times.

[0013] Preferably, it also includes the step of monitoring the bandwidth, delay and packet loss rate of the network transmission network of the network topology structure at different unit times. The step of monitoring the bandwidth, delay and packet loss rate of the network transmission network of the network topology structure at different unit times is that the computing resource computing power optimization module transmits the monitoring instructions of the bandwidth, delay and packet loss rate of the network transmission network of the network topology structure at different unit times to the monitoring module of the bandwidth, delay and packet loss rate of the network transmission network of the network topology structure at different unit times. The monitoring module of the bandwidth, delay and packet loss rate of the network transmission network of the network topology structure at different unit times regulates the bandwidth, delay and packet loss rate of the network transmission network of the network topology structure at different unit times of the current task according to the received instructions. Beneficial effects: The computing power optimization method and system for cloud computing data center transmission provided by the present invention solve the problems of complex detection, difficult monitoring, and uncontrollable computing power system in the current methods for detecting the bandwidth, delay, and packet loss rate of network topology structures transmitted in different unit times, and provide a system for detecting the bandwidth, delay, and packet loss rate of network topology structures transmitted in different unit times with a simple structure, simple operation, and simple analysis, which can be easily and accurately monitored and can be used for multi-regional detection system analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0015] Figure 1 This is a structural diagram of the computing power optimization system used for cloud computing data center transmission; Figure 2 A flow chart of a method for optimizing computing power for cloud computing data center transmission. DETAILED DESCRIPTION

[0016] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present invention. However, it should be clear to those skilled in the art that the present invention may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present invention.

[0017] like Figure 1 As shown, the present invention provides a computing power optimization system for cloud computing data center transmission, including a network parameter integration module and a computing resource computing power optimization module; The network parameter integration module is set in the cloud computing data center monitoring task. The network parameter integration module pre-stores the benchmark traffic load and transmission network bandwidth, delay, and packet loss rate of network topology structures at different unit times. The traffic load and transmission network bandwidth, delay, and packet loss rate of network topology structures at different unit times are collected through the traffic analyzer module. The network fault tolerance rate is obtained by comparing the traffic load and transmission network bandwidth, delay, and packet loss rate of network topology structures at different unit times with the benchmark traffic load and transmission network bandwidth, delay, and packet loss rate. The calculation and analysis results are obtained by comparing the data throughput and the network fault tolerance rate. The service response time is calculated for the transmission network bandwidth, delay, and packet loss rate of network topology structures at different unit times. The transmission network bandwidth, delay, and packet loss rate of network topology structures at different unit times include the calculation and analysis results, the benchmark traffic load and transmission network bandwidth, delay, packet loss rate, and network fault tolerance rate. The computing resource and computing power optimization module obtains and displays the transmission network bandwidth, latency, and packet loss rate of the network topology structure at different unit times. It allocates and executes tasks by real-time monitoring of the resource utilization of computing nodes and combining intelligent scheduling and load balancing strategies. At the same time, it dynamically adjusts computing resources and task migration technology to reduce energy consumption by balancing resource utilization and energy consumption optimization.

[0018] The network parameter integration module includes a traffic analyzer module monitoring unit, a CPU operating frequency limiting unit and a task queue management unit. The traffic analyzer module monitoring unit obtains the network topology traffic load and transmission network bandwidth, delay, and packet loss rate of different unit times through the CPU system, and transmits them to the CPU operating frequency limiting unit. The CPU operating frequency limiting unit receives the network topology traffic load and transmission network bandwidth, delay, and packet loss rate of different unit times and compares them with the pre-stored benchmark traffic load and transmission network bandwidth, delay, and packet loss rate, calculates the network fault tolerance rate between the two, and compares the network fault tolerance rate with the data throughput. When the network fault tolerance rate is greater than the data throughput, the calculation and analysis results are obtained that the network topology structures of different unit times are subject to the transmission network bandwidth, delay, and packet loss rate of the network topology structures of different unit times. The task queue management unit receives the network fault tolerance rate and calculation and analysis results issued by the server control unit, and calculates the service response time for the received network topology transmission network bandwidth, delay, and packet loss rate of the network topology structures of different unit times. The CPU operating frequency limiting unit stores the standard fluctuation range and the network topology structures of different unit times of transmission network bandwidth, delay, and packet loss rate. The traffic analyzer module monitoring unit obtains the current fluctuation range and the network topology structures of different unit times of transmission network bandwidth, delay, and packet loss rate. The data throughput is the network fault tolerance rate between the network topology structures of different unit times to be detected without the network topology structures of different unit times and the transmission network bandwidth, delay, and packet loss rate, and the benchmark traffic load and the transmission network bandwidth, delay, and packet loss rate.The network parameter integration module can calculate and analyze the network bandwidth, delay and packet loss rate of network topology structures at different unit times for monitoring tasks of cloud computing data centers by calculating and analyzing the network fault tolerance rate between network topology structures at different unit times and transmission network bandwidth, delay and packet loss rate, and the benchmark traffic load and transmission network bandwidth, delay and packet loss rate. There is no need to set up a test signal transceiver, and the hardware structure is simple. The network parameter integration module directly collects the network topology traffic load and transmission network bandwidth, delay and packet loss rate of network topology structures at different unit times through the traffic analyzer module. No manual intervention is required, and the operation is simple. In addition, the network bandwidth, delay and packet loss rate of network topology structures at different unit times can be calculated and analyzed by calculating the distance of the transmission network bandwidth, delay and packet loss rate. The analysis is simple, and because the present invention Ming calculates and analyzes the network bandwidth, delay and packet loss rate of network topology structures at different unit times through the traffic load of network topology structures at different unit times and the transmission network bandwidth, delay and packet loss rate. Therefore, when detecting the network bandwidth, delay and packet loss rate of network topology structures at different unit times, the network topology structure information at different unit times is obtained, and there is no problem that the network bandwidth, delay and packet loss rate of network topology structures at different unit times is difficult to monitor. The network bandwidth, delay and packet loss rate of network topology structures at different unit times are transmitted through the task queue management unit, so that the computing resource computing power optimization module can obtain the network bandwidth, delay and packet loss rate of network topology structures at different unit times, and realizes the network bandwidth, delay and packet loss rate detection system of network topology structures at different unit times analyzed by multi-region detection system.

[0019] The traffic analyzer module monitoring unit includes a CPU frequency monitoring module, which works under the control of the CPU operating frequency limiting unit. The CPU frequency monitoring module reduces the impact of abnormal transmission network bandwidth, delay, and packet loss rate of network topology structures in different unit times on the traffic analyzer module monitoring. The CPU frequency monitoring module can regulate the network bandwidth, delay and packet loss rate of the network topology transmission structure with different unit time that the traffic analyzer module monitoring unit is subject to. Since the CPU frequency monitoring module regulates the network bandwidth, delay and packet loss rate of the network topology transmission structure with different unit time of the monitoring unit, the monitoring effect of the traffic analyzer module monitoring unit can be improved under the monitoring of the network bandwidth, delay and packet loss rate of the network topology transmission structure with different unit time. Therefore, when the monitoring effect of the CPU frequency monitoring module is increased, the monitoring effect of the traffic analyzer module monitoring unit will not be greatly affected under larger network bandwidth, delay and packet loss rate of the network topology transmission structure with different unit time. Therefore, the network parameter integration module reduces the traffic load of the network topology transmission structure with different unit time bandwidth, delay and packet loss rate, and can be used in situations where there is a certain tolerance for the network bandwidth, delay and packet loss rate of the network topology transmission structure with different unit time. On the contrary, when the monitoring effect of the CPU frequency monitoring module is reduced, the monitoring effect of the traffic analyzer module monitoring unit will also be greatly affected under smaller different unit time network topology transmission network bandwidth, delay, and packet loss rate. Therefore, the network parameter integration module increases the network topology traffic load of different unit time network topology transmission network bandwidth, delay, and packet loss rate, which can be applied to the fluctuation range of network bandwidth, delay, and packet loss rate of different unit time network topology transmission network bandwidth. In the present invention, the computing resource computing power optimization module can control the monitoring effect of the CPU frequency monitoring module by issuing instructions, thereby controlling the network parameter integration module for the network topology traffic load of different unit time network topology transmission network bandwidth, delay, and packet loss rate, so that the system is applicable to various different environments.

[0020] The task queue management unit is a CPU cache size transmission unit. The CPU cache size transmission unit transmits calculation and analysis results, network fault tolerance and benchmark traffic load, and transmission network bandwidth, delay, and packet loss rate to the CPU system. The computing resource computing power optimization module receives data through the CPU system. The CPU system independently developed by my country has broken through the technical limitation that the ground service station can only receive CPU signals in traditional CPU transmission, but cannot realize the two-way information transmission of the CPU, realizes the two-way transmission of the CPU, and supports the transmission of cache size. The present invention utilizes the cache size transmission function of the CPU system, and by setting the CPU cache size transmission unit, uses the CPU system to realize the two-way transmission between the network parameter integration module and the computing resource computing power optimization module, without setting other transmission methods, making the transmission between systems simpler and more convenient.

[0021] The computing power optimization system for cloud computing data center transmission provided by the present invention also includes a thread number management module. The computing resource computing power optimization module analyzes the obtained calculation and analysis results, network fault tolerance and benchmark traffic load, and transmission network bandwidth, delay, and packet loss rate, generates transmission network bandwidth, delay, and packet loss rate status data of network topology structures with different unit times, and transmits them to the specified thread number management module; any thread number management module transmits a request to the computing resource computing power optimization module to obtain the transmission network bandwidth, delay, and packet loss rate of network topology structures with different unit times for cloud computing data center monitoring tasks.

[0022] The present invention generates network bandwidth, delay, and packet loss rate status data of network topology transmission at different unit times through a computing resource computing power optimization module, and transmits the network bandwidth, delay, and packet loss rate status data of network topology transmission at different unit times to a designated thread number management module. The designated thread number management module of the present invention refers to a thread number management module that is responsible for managing tasks of network bandwidth, delay, and packet loss rate of network topology transmission at different unit times. For example, the cloud computing data center monitoring task is cloud computing data center D, street C, district B, city A. When the cloud computing data center monitoring task is subject to network bandwidth, delay, and packet loss rate of network topology transmission at different unit times, the computing resource computing power optimization module transmits the network bandwidth, delay, and packet loss rate status data of network topology transmission at different unit times to the thread number management module of street C. Relevant management personnel can timely receive the network bandwidth, delay, and packet loss rate status data of network topology transmission at different unit times and confirm the status of the current cloud computing data center monitoring task and make corresponding responses. At the same time, any thread number management module can actively access the computing resource and computing power optimization module to obtain the network bandwidth, latency, and packet loss rate of the network topology structure transmission per unit time for all or specified cloud computing data center monitoring tasks, so that managers can monitor related tasks more actively.

[0023] The computing power optimization system for cloud computing data center transmission provided by the present invention also includes: a monitoring module for network bandwidth, delay, and packet loss rate of network topology structures transmitted per unit time. The monitoring module for network bandwidth, delay, and packet loss rate of network topology structures transmitted per unit time receives instructions transmitted by the server to regulate the network bandwidth, delay, and packet loss rate of network topology structures transmitted per unit time of the current task.

[0024] The present invention improves the transmission network bandwidth, delay and packet loss rate of network topology structures with different unit times of the task by setting up monitoring modules for the transmission network bandwidth, delay and packet loss rate of network topology structures with different unit times. It can respond quickly under the control of the computing resource computing power optimization module, improve the ecological environment in time, avoid the danger caused by the transmission network bandwidth, delay and packet loss rate of network topology structures with different unit times, and buy precious time for emergency repair when serious transmission network bandwidth, delay and packet loss rate of network topology structures with different unit times occur.

[0025] like Figure 2 As shown, the computing power optimization method for cloud computing data center transmission provided by the present invention includes the following steps: S100, setting a network parameter integration module in all cloud computing data center monitoring tasks, pre-storing the benchmark traffic load of network topology structures at different unit times and the transmission network bandwidth, delay, and packet loss rate in the network parameter integration module; S200, the network parameter integration module collects the network topology traffic load and transmission network bandwidth, delay, and packet loss rate of different unit time through the traffic analyzer module, and compares the network topology traffic load and transmission network bandwidth, delay, and packet loss rate of different unit time with the benchmark traffic load and transmission network bandwidth, delay, and packet loss rate to obtain the network fault tolerance rate; S300, the network parameter integration module compares the data throughput and the network fault tolerance rate to obtain the calculation and analysis results, calculates the service response time for the transmission network bandwidth, delay, and packet loss rate of the network topology structure at different unit times, and the transmission network bandwidth, delay, and packet loss rate of the network topology structure at different unit times include the calculation and analysis results, the benchmark traffic load and the transmission network bandwidth, delay, packet loss rate, and network fault tolerance rate; S400, the computing resource and computing power optimization module obtains and displays the network bandwidth, latency, and packet loss rate of the network topology structure at different unit times. It allocates and executes tasks by real-time monitoring of the resource utilization of computing nodes and combining intelligent scheduling and load balancing strategies. At the same time, it dynamically adjusts computing resources and task migration technology to reduce energy consumption by balancing resource utilization and energy consumption optimization.

[0026] The present invention realizes the system management of the transmission network bandwidth, delay, and packet loss rate of network topology structures with different unit time in multiple regions by setting a network parameter integration module and a computing resource computing power optimization module. The network parameter integration module collects the traffic load of network topology structures with different unit time and the transmission network bandwidth, delay, and packet loss rate through the traffic analyzer module, compares the traffic load of network topology structures with different unit time and the transmission network bandwidth, delay, and packet loss rate with the benchmark traffic load and the transmission network bandwidth, delay, and packet loss rate, and obtains the calculation and analysis results by comparing with the data throughput. Since the CPU signal is not amplified during the transmission process, the CPU signal is relatively weak and is easily affected by the transmission network bandwidth, delay, and packet loss rate of network topology structures with different unit time. Therefore, when using CPU monitoring, it is easy to be affected by the transmission network bandwidth, delay, and packet loss rate of network topology structures with different unit time, which may lead to inaccurate monitoring.

[0027] The present invention sets a network parameter integration module in the cloud computing data center monitoring task, and pre-stores the benchmark traffic load and transmission network bandwidth, delay, and packet loss rate in the network parameter integration module, and collects network topology structures of different unit time through the traffic analyzer module. Since the traffic analyzer module monitoring uses CPU signal transmission, it is easily affected by the transmission network bandwidth, delay, and packet loss rate of network topology structures of different unit time. Therefore, if the cloud computing data center monitoring task has the transmission network bandwidth, delay, and packet loss rate of network topology structures of different unit time, the traffic load of network topology structures of different unit time and the transmission network bandwidth, delay, and packet loss rate collected by the traffic analyzer module will have a large deviation from the pre-stored benchmark traffic load and the transmission network bandwidth, delay, and packet loss rate. Therefore, the present invention can calculate and analyze the transmission network bandwidth, delay and packet loss rate of network topology structures with different unit times of cloud computing data center monitoring tasks by calculating and analyzing the network fault tolerance rate between the network topology structures with different unit times and the transmission network bandwidth, delay and packet loss rate and the benchmark traffic load and the transmission network bandwidth, delay and packet loss rate. In the present invention, the network topology structures with different unit times of cloud computing data center monitoring tasks are used as test signals, the benchmark traffic load and the transmission network bandwidth, delay and packet loss rate are equivalent to the original test signals, the network topology structures with different unit times and the transmission network bandwidth, delay and packet loss rate obtained through the CPU signal are equivalent to the received test signals, and the comparative analysis of the test signals is realized by comparing the network topology structures with different unit times and the transmission network bandwidth, delay and packet loss rate with the pre-stored benchmark traffic load and the transmission network bandwidth, delay and packet loss rate. It is not necessary to set up a test signal receiving and sending device, and the hardware structure is simple. The network parameter integration module directly collects the network topology traffic load and the transmission network bandwidth, delay, and packet loss rate of different unit times through the traffic analyzer module. No manual intervention is required, and the operation is simple. The transmission network bandwidth, delay, and packet loss rate of different unit times of the network topology can be calculated and analyzed by calculating the distance of the transmission network bandwidth, delay, and packet loss rate. The analysis is simple. Moreover, since the present invention calculates and analyzes the transmission network bandwidth, delay, and packet loss rate of different unit times of the network topology traffic load and the transmission network bandwidth, delay, and packet loss rate of different unit times of the network topology, the network topology information of different unit times is obtained when the transmission network bandwidth, delay, and packet loss rate of the network topology of different unit times is detected, and there is no problem that the transmission network bandwidth, delay, and packet loss rate of the network topology of different unit times is difficult to monitor.

[0028] The present invention solves the problems of complex detection, difficult monitoring, and uncontrollable computing system in the current methods for detecting the bandwidth, delay, and packet loss rate of network transmission networks with different unit time topologies, and provides a method for detecting the bandwidth, delay, and packet loss rate of network transmission networks with different unit time topologies that is simple in structure, simple in operation, simple in analysis, and can be easily and accurately monitored and can be analyzed by a multi-regional detection system.

[0029] The computing power optimization method for cloud computing data center transmission provided by the present invention also includes: step S500, the computing resource computing power optimization module obtains the transmission network bandwidth, delay, and packet loss rate of network topology structures with different unit times, generates the transmission network bandwidth, delay, and packet loss rate status data of network topology structures with different unit times according to the transmission network bandwidth, delay, and packet loss rate of network topology structures with different unit times, and determines the different unit time network topology structures with different unit time network topology structure transmission network bandwidth, delay, and packet loss rate tasks through the benchmark traffic load and the transmission network bandwidth, delay, and packet loss rate, and transmits the transmission network bandwidth, delay, and packet loss rate status data of the network topology structures with different unit times to the thread number management module that manages the transmission network bandwidth, delay, and packet loss rate tasks of the network topology structures with different unit times.

[0030] The present invention generates network bandwidth, delay, and packet loss rate status data of network topology transmission with different unit time through a computing resource computing power optimization module, and transmits the network bandwidth, delay, and packet loss rate status data of network topology transmission with different unit time to a designated thread number management module. The designated thread number management module of the present invention refers to a thread number management module that has management obligations for tasks affected by network bandwidth, delay, and packet loss rate of network topology transmission with different unit time. For example, the cloud computing data center monitoring task is cloud computing data center D, street C, district B, city A. When the cloud computing data center monitoring task is affected by network bandwidth, delay, and packet loss rate of network topology transmission with different unit time, the computing resource computing power optimization module transmits the network bandwidth, delay, and packet loss rate status data of network topology transmission with different unit time to the thread number management module of street C. Relevant management personnel can timely receive the network bandwidth, delay, and packet loss rate status data of network topology transmission with different unit time, confirm the status of the current cloud computing data center monitoring task, and make corresponding responses. At the same time, any thread number management module can actively access the computing resource and computing power optimization module to obtain the network bandwidth, latency, and packet loss rate of the network topology structure transmission per unit time for all or specified cloud computing data center monitoring tasks, so that managers can monitor related tasks more actively.

[0031] It also includes: a step of adjusting the traffic load of the network topology structure at different unit times. The step of adjusting the traffic load of the network topology structure at different unit times is that the computing resource computing power optimization module transmits the CPU frequency monitoring instruction to the network parameter integration module, and the network parameter integration module adjusts the network bandwidth, delay, and packet loss rate fluctuation range of the network topology structure transmission of the CPU frequency monitoring module at different unit times. The present invention regulates the network bandwidth, delay and packet loss rate of the network topology structure transmission per unit time of the traffic analyzer module monitoring unit through the CPU frequency monitoring module. Since the CPU frequency monitoring module regulates the network bandwidth, delay and packet loss rate of the network topology structure transmission per unit time of the monitoring unit, the monitoring effect of the traffic analyzer module monitoring unit can be improved under the action of monitoring the network bandwidth, delay and packet loss rate of the network topology structure transmission per unit time. Therefore, when the monitoring effect of the CPU frequency monitoring module is increased, the monitoring effect of the traffic analyzer module monitoring unit will not be greatly affected under larger network bandwidth, delay and packet loss rate of the network topology structure transmission per unit time. Therefore, the network parameter integration module reduces the network topology structure traffic load per unit time of the network topology structure transmission bandwidth, delay and packet loss rate, and can be applied to the situation where the network topology structure transmission bandwidth, delay and packet loss rate per unit time has a certain tolerance. On the contrary, when the monitoring effect of the CPU frequency monitoring module is reduced, the monitoring effect of the traffic analyzer module monitoring unit will also be greatly affected under smaller different unit time network topology transmission network bandwidth, delay, and packet loss rate. Therefore, the network parameter integration module increases the network topology traffic load of different unit time network topology transmission network bandwidth, delay, and packet loss rate, which can be applied to the situation of fluctuation range of network bandwidth, delay, and packet loss rate of different unit time network topology transmission network bandwidth. In the present invention, the computing resource computing power optimization module can control the monitoring effect of the CPU frequency monitoring module by issuing instructions, thereby controlling the network parameter integration module for the network topology traffic load of different unit time network topology transmission network bandwidth, delay, and packet loss rate, so that the method is applicable to various different environments.

[0032] It also includes: the steps of monitoring the bandwidth, delay and packet loss rate of the network topology transmission network at different unit times, and the steps of monitoring the bandwidth, delay and packet loss rate of the network topology transmission network at different unit times are: the computing resource computing power optimization module transmits the monitoring instructions of the bandwidth, delay and packet loss rate of the network topology transmission network at different unit times to the monitoring module of the network topology transmission network at different unit times, and the monitoring module of the network topology transmission network at different unit times regulates the bandwidth, delay and packet loss rate of the network topology transmission network at different unit times of the current task according to the received instructions. The present invention sets the monitoring module of the bandwidth, delay and packet loss rate of the network topology transmission network at different unit times to improve the status of the network topology transmission network at different unit times of the task, which can respond quickly under the control of the computing resource computing power optimization module, improve the ecological environment in time, avoid the risks brought by the abnormalities of the bandwidth, delay and packet loss rate of the network topology transmission network at different unit times, and can also buy precious time for emergency repair when the bandwidth, delay and packet loss rate of the network topology transmission network at different unit times seriously occurs.

[0033] The above are preferred embodiments of the present invention. It should be noted that, for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A computing power optimization system for cloud computing data center transmission, characterized in that: Includes network parameter integration module and computing resource power optimization module; The network parameter integration module is set in the cloud computing data center monitoring task, and the network parameter integration module pre-stores the benchmark traffic load and transmission network bandwidth, delay, and packet loss rate of network topology structures at different unit times, collects the traffic load and transmission network bandwidth, delay, and packet loss rate of network topology structures at different unit times through the traffic analyzer module, compares the traffic load and transmission network bandwidth, delay, and packet loss rate of network topology structures at different unit times with the benchmark traffic load and transmission network bandwidth, delay, and packet loss rate to obtain the network fault tolerance rate, obtains the calculation and analysis results by comparing the data throughput and the network fault tolerance rate, and calculates the service response time for the transmission network bandwidth, delay, and packet loss rate of network topology structures at different unit times; wherein, the transmission network bandwidth, delay, and packet loss rate of network topology structures at different unit times include the calculation and analysis results, the benchmark traffic load and transmission network bandwidth, delay, packet loss rate, and network fault tolerance rate; The computing resource power optimization module obtains and displays the network bandwidth, latency, and packet loss rate of the network topology structure transmission at different unit times, and distributes and executes tasks by real-time monitoring of the resource utilization of computing nodes, combined with intelligent scheduling and load balancing strategies. At the same time, by balancing resource utilization and energy consumption optimization, it dynamically adjusts computing resources and task migration technology to reduce energy consumption.

2. The computing power optimization system for cloud computing data center transmission according to claim 1, characterized in that: The network parameter integration module includes a traffic analyzer module monitoring unit, a CPU operating frequency limiting unit and a task queue management unit. The traffic analyzer module monitoring unit obtains the network topology traffic load and transmission network bandwidth, delay, and packet loss rate of different unit times through the CPU system, and transmits them to the CPU operating frequency limiting unit. The CPU operating frequency limiting unit receives the network topology traffic load and transmission network bandwidth, delay, and packet loss rate of different unit times and compares them with the pre-stored benchmark traffic load and transmission network bandwidth, delay, and packet loss rate, calculates the network fault tolerance rate between the two, and compares the network fault tolerance rate with the data throughput. When the network fault tolerance rate is greater than the data throughput, the calculation and analysis results are obtained that the network topology structures of different unit times are subject to the transmission network bandwidth, delay, and packet loss rate of the network topology structures of different unit times. The task queue management unit receives the network fault tolerance rate and the calculation and analysis results issued by the server control unit, and calculates the service response time for the received network topology transmission network bandwidth, delay, and packet loss rate of the network topology structures of different unit times.

3. The computing power optimization system for cloud computing data center transmission according to claim 2, characterized in that: The traffic analyzer module monitoring unit includes a CPU frequency monitoring module, which works under the control of a CPU operating frequency limiting unit. The CPU frequency monitoring module reduces the impact of abnormal transmission network bandwidth, delay, and packet loss rate of network topology structures in different unit times on the traffic analyzer module monitoring.

4. The computing power optimization system for cloud computing data center transmission according to claim 2, characterized in that: The task queue management unit is a CPU cache size transmission unit, which transmits calculation and analysis results, network fault tolerance and benchmark traffic load, and transmission network bandwidth, latency, and packet loss rate to the CPU system. The computing resource computing power optimization module receives data through the CPU system.

5. The computing power optimization system for cloud computing data center transmission according to claim 1, characterized in that: Also includes: The thread number management module, the computing resource computing power optimization module analyzes the obtained calculation and analysis results, network fault tolerance and benchmark traffic load, and transmission network bandwidth, delay, and packet loss rate, generates transmission network bandwidth, delay, and packet loss rate status data of network topology structures in different unit time, and transmits them to the specified thread number management module; The arbitrary thread number management module transmits a request to the computing resource computing power optimization module to obtain the network bandwidth, delay, and packet loss rate of the network topology structure of different unit times for the cloud computing data center monitoring task.

6. The computing power optimization system for cloud computing data center transmission according to claim 1, characterized in that: It also includes: a monitoring module for the network bandwidth, delay, and packet loss rate of the network topology structure transmission at different unit times. The monitoring module for the network bandwidth, delay, and packet loss rate of the network topology structure transmission at different unit times receives instructions transmitted by the server to adjust the network bandwidth, delay, and packet loss rate of the network topology structure transmission at different unit times of the current task.

7. A computing power optimization method for cloud computing data center transmission, characterized in that: The following steps are involved: S100, setting a network parameter integration module in all cloud computing data center monitoring tasks, pre-storing the benchmark traffic load of network topology structures at different unit times and the transmission network bandwidth, delay, and packet loss rate in the network parameter integration module; S200, the network parameter integration module collects the network topology traffic load and transmission network bandwidth, delay, and packet loss rate of different unit time through the traffic analyzer module, and compares the network topology traffic load and transmission network bandwidth, delay, and packet loss rate of different unit time with the benchmark traffic load and transmission network bandwidth, delay, and packet loss rate to obtain the network fault tolerance rate; S300, the network parameter integration module compares the data throughput and the network fault tolerance rate to obtain calculation and analysis results, and calculates the service response time for the transmission network bandwidth, delay, and packet loss rate of the network topology structure with different unit time, wherein the transmission network bandwidth, delay, and packet loss rate of the network topology structure with different unit time include calculation and analysis results, benchmark traffic load, and transmission network bandwidth, delay, packet loss rate, and network fault tolerance rate; S400, computing resource computing power optimization module obtains and displays the network bandwidth, delay, and packet loss rate of the network topology structure transmission in different unit time, and distributes and executes tasks by real-time monitoring of the resource utilization of computing nodes, combined with intelligent scheduling and load balancing strategies. At the same time, through the balance of resource utilization and energy consumption optimization, it dynamically adjusts computing resources and task migration technology to reduce energy consumption; S500, the computing resource computing power optimization module obtains the transmission network bandwidth, delay and packet loss rate of network topology structures with different unit times, generates the transmission network bandwidth, delay and packet loss rate status data of network topology structures with different unit times according to the transmission network bandwidth, delay and packet loss rate of network topology structures with different unit times, and determines the different unit time network topologies with different unit time network topology structure transmission network bandwidth, delay and packet loss rate tasks through the benchmark traffic load and transmission network bandwidth, delay and packet loss rate, and transmits the transmission network bandwidth, delay and packet loss rate status data of network topology structures with different unit times to the thread number management module that manages the transmission network bandwidth, delay and packet loss rate tasks of network topology structures with different unit times.

8. The computing power optimization method for cloud computing data center transmission according to claim 7, characterized in that: It also includes: a step of adjusting the traffic load of the network topology structure at different unit times, wherein the step of adjusting the traffic load of the network topology structure at different unit times is that the computing resource computing power optimization module transmits the CPU frequency monitoring instruction to the network parameter integration module, and the network parameter integration module adjusts the network bandwidth, delay, and packet loss rate fluctuation range of the network topology structure transmission of the CPU frequency monitoring module at different unit times.

9. The computing power optimization method for cloud computing data center transmission according to claim 7, characterized in that: The method also includes: a step of monitoring the bandwidth, delay and packet loss rate of the network transmission network of the network topology structure at different unit times, wherein the step of monitoring the bandwidth, delay and packet loss rate of the network transmission network of the network topology structure at different unit times is that the computing resource computing power optimization module transmits the monitoring instruction of the bandwidth, delay and packet loss rate of the network transmission network of the network topology structure at different unit times to the monitoring module of the bandwidth, delay and packet loss rate of the network transmission network of the network topology structure at different unit times, and the monitoring module of the bandwidth, delay and packet loss rate of the network transmission network of the network topology structure at different unit times regulates the bandwidth, delay and packet loss rate of the network transmission network of the network topology structure at different unit times of the current task according to the received instruction.

Images