Distributed system optimization control method and system based on central cluster test management

Abstract

The invention discloses a distributed system optimization control method and system based on central cluster test management, and relates to the technical field of distributed systems. The distributed system optimization control method based on central cluster test management comprises the following steps: receiving registration information, initial state information and capability parameter information of each distributed system node; establishing a basic communication network through a cross-domain communication bridge according to the registration information of each distributed system node; and sending a performance data collection request to each registered distributed system node according to preset time. According to the method and the device, the problems that in the prior art, a distributed system still has defects in the aspects of real-time monitoring and comprehensive optimization of system performance, a management system of an edge device cluster mainly pays attention to management of edge devices, and the requirements of the distributed system as a whole in the aspect of performance optimization are not fully met are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of distributed systems, and in particular to a distributed system optimization control method and system based on central cluster test management. Background Art

[0002] With the rapid development of information technology, distributed systems are widely used in various industries due to their efficient data processing capabilities, powerful storage functions and high reliability. Distributed systems can significantly improve processing speed and system stability by distributing computing tasks on multiple nodes. However, as the scale of the system expands and the application scenarios become more complex, how to effectively manage and optimize the performance of these distributed systems has become a challenge.

[0003] Among the existing technologies, some technologies explain a method for information processing of a distributed system involving information synchronization and verification mechanisms between member nodes, and emphasize the application of smart contracts in maintaining data consistency and executing operations. Although this method improves the data processing efficiency and security of distributed systems, it still has shortcomings in real-time monitoring and comprehensive optimization of system performance. Other technologies provide a management system for edge device clusters, which realizes effective management of edge device clusters by deploying agents and device management software on edge devices and communicating with central clusters. This technology improves the configuration and instruction execution efficiency of edge device clusters through centralized management strategies. However, this method mainly focuses on the management of edge devices and does not fully address the performance optimization needs of distributed systems as a whole.

[0004] In view of the fact that the existing distributed systems still have deficiencies in real-time monitoring and comprehensive optimization of system performance, and the management system of the edge device cluster mainly focuses on the management of edge devices, and does not fully solve the problem of performance optimization requirements of the distributed system as a whole. No effective solution has been proposed for the above problems. Summary of the invention

[0005] Purpose of the invention: To provide a distributed system optimization control method and system based on central cluster test management to solve the above problems existing in the prior art.

[0006] Technical solution: A distributed system optimization control method based on central cluster test management includes the following steps:

[0007] Receive registration information, initial status information and capability parameter information of each distributed system node;

[0008] Establish a basic communication network through a cross-domain communication bridge based on the registration information of each distributed system node;

[0009] Sending a performance data collection request to each registered distributed system node at a preset time;

[0010] Receive and analyze performance data from each distributed system node, and evaluate the health and performance status of the entire distributed system based on the analysis results;

[0011] Based on the evaluation results, identify the distributed system nodes that need to be optimized or adjusted, and formulate corresponding optimization strategies;

[0012] The optimization strategy is converted into specific execution instructions and sent to the corresponding distributed system nodes to guide the system nodes to perform self-optimization and adjustment.

[0013] Preferably, before receiving the registration information, initial state information and capability parameter information of each distributed system node, the method further includes:

[0014] Initialize the central cluster test management platform.

[0015] As a preferred option, the central cluster test management platform includes:

[0016] The IP address and port number of each distributed system node, the hardware configuration of each node, the software environment, predefined performance monitoring indicators and warning thresholds.

[0017] Preferably, the central cluster test management platform is initialized, including:

[0018] Installation and deployment of software, loading of configuration files, startup of necessary services and initial status check.

[0019] Preferably, receiving registration information, initial state information and capability parameter information of each distributed system node includes:

[0020] When registering, a compute node reports its current CPU usage and the number of tasks being executed, as well as its CPU model, number of cores, and the maximum number of concurrent tasks it can carry as its initial state and capability parameters;

[0021] Storage nodes report the usage of their storage space and the amount of data currently stored, and provide total storage capacity, read and write speeds, and supported storage protocols to describe their capabilities;

[0022] The network node reports the current network traffic and number of connections, as well as the maximum throughput, supported network protocols and latency performance to summarize its network processing capabilities;

[0023] The service node reports the current operating status and service response time of the service, as well as the type of service that can be provided, concurrent processing capabilities, and software and hardware environment.

[0024] Preferably, a basic communication network is established through a cross-domain communication bridge according to the registration information of each distributed system node, including:

[0025] After receiving the registration information of each distributed system node, analyzing the network configuration and capability parameters of each node; wherein the network configuration includes: IP address, port number and supported network protocol;

[0026] Based on the analysis results, determine the topology of the network; wherein the topology includes: the connection mode between nodes, the data transmission path and the routing strategy;

[0027] Configure cross-domain communication bridges, set bridging rules and data forwarding strategies;

[0028] Sending a network configuration instruction to each distributed system node through a cross-domain communication bridge; wherein the network configuration instruction includes: a specified IP address, a port number, a network protocol, and authentication information;

[0029] Each distributed system node adjusts its network settings according to the received network configuration instructions and completes the connection and registration with the cross-domain communication bridge;

[0030] After the establishment of the basic communication network is completed, communication testing is carried out through the cross-domain communication bridge to verify the connectivity, stability and performance indicators of the network.

[0031] Preferably, receiving and analyzing performance data from each distributed system node, and evaluating the health status and performance status of the entire distributed system based on the analysis results, including:

[0032] Receive and analyze performance data from each distributed system node, wherein the performance data includes: CPU usage C, memory usage M, disk I / O rate S, network throughput D;

[0033] The normal operation thresholds of each performance indicator are predefined as follows: CPU usage does not exceed α, memory usage does not exceed β, disk I / O rate is lower than χ per second, and network throughput reaches at least φ;

[0034] The calculation formula of health score HS is:

[0035]

[0036]

[0037]

[0038]

[0039]

[0040] Among them, α, β, χ, and φ represent thresholds.

[0041] Preferably, the distributed system nodes that need to be optimized or adjusted are identified based on the evaluation results, and corresponding optimization strategies are formulated, including:

[0042] When the CPU usage exceeds α and HS is less than 1, the computing node is downgraded;

[0043] When the memory usage exceeds β and HS is less than 1, the storage node is downgraded;

[0044] When the disk I / O rate exceeds χ and HS is less than 1, the storage node is downgraded;

[0045] When the network throughput is lower than φ and HS is less than 1, the network nodes are increased.

[0046] In order to achieve the above objective, according to another aspect of the present application, a distributed system optimization control system based on central cluster test management is provided.

[0047] The distributed system optimization control system based on central cluster test management according to the present application includes:

[0048] A receiving module, used to receive registration information, initial status information and capability parameter information of each distributed system node;

[0049] Establishing a basic communication network module, which is used to establish a basic communication network through a cross-domain communication bridge according to the registration information of each distributed system node;

[0050] The performance data collection request module is used to send performance data collection requests to each registered distributed system node according to a preset time;

[0051] The analysis and evaluation module is used to receive and analyze the performance data from each distributed system node, and evaluate the health status and performance status of the entire distributed system based on the analysis results;

[0052] Identify and formulate optimization strategy module, which is used to identify the distributed system nodes that need to be optimized or adjusted based on the evaluation results, and formulate corresponding optimization strategies;

[0053] The sending guidance module is used to convert the optimization strategy into specific execution instructions, which are sent to the corresponding distributed system nodes to guide the system nodes to perform self-optimization and adjustment.

[0054] In order to achieve the above-mentioned purpose, according to another aspect of the present application, an electronic device is provided, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the distributed system optimization control method based on central cluster test management as described in any one of the present invention.

[0055] Beneficial effect: In the embodiment of the present application, a distributed system optimization control method based on central cluster test management is adopted, by receiving the registration information, initial state information and capability parameter information of each distributed system node; establishing a basic communication network through a cross-domain communication bridge according to the registration information of each distributed system node; issuing a performance data collection request to each registered distributed system node at a preset time; receiving and analyzing the performance data from each distributed system node, and evaluating the health status and performance status of the entire distributed system based on the analysis results; identifying the distributed system nodes that need to be optimized or adjusted based on the evaluation results, and formulating corresponding optimization strategies; converting the optimization strategies into specific execution instructions, sending them to the corresponding distributed system nodes, guiding the system nodes to perform self-optimization and adjustment, achieving the purpose of supporting dynamic optimization and adaptive adjustment, thereby achieving the technical effect of improving system performance and stability, and further solving the problems in the existing technology that the distributed system still has deficiencies in real-time monitoring and comprehensive optimization of system performance, and that the management system of the edge device cluster mainly focuses on the management of edge devices, and does not fully solve the technical problems of the performance optimization requirements of the distributed system as a whole.

[0056] Compared with the related prior art, the present invention has at least the following main technical advantages, and the beneficial effects of the present invention are:

[0057] Improve system performance and stability: By real-time monitoring of the performance data of each node in the distributed system and formulating optimization strategies based on data analysis, the present invention can effectively prevent the occurrence of performance bottlenecks and reduce the system failure rate, thereby significantly improving the overall performance and stability of the system.

[0058] Optimize resource utilization: By precisely controlling resource allocation and task scheduling, efficient resource utilization is ensured. By avoiding over-allocation or waste of resources, it helps enterprises reduce operating costs and improve return on investment.

[0059] Support dynamic optimization and adaptive adjustment: With the help of advanced data analysis and decision-making engines, it can dynamically adjust the optimization strategy according to the system operation status and performance data, realize adaptive optimization, and ensure that the system maintains the best performance in a constantly changing operating environment.

[0060] Simplify system management and maintenance: Through centralized test management and optimized control, the complexity of system management and maintenance workload are reduced, allowing system administrators to monitor and manage the entire distributed system more conveniently.

[0061] Improve the scalability and flexibility of the system: The method of the present invention is not only applicable to the current system architecture and technology stack, but its design principles and implementation mechanisms are also applicable to future technology evolution and system expansion, ensuring long-term application value and flexibility.

[0062] In summary, the present invention, by providing an efficient and intelligent distributed system optimization control method, not only solves the performance optimization and resource management problems existing in the prior art, but also provides strong support for the stable operation and sustainable development of the distributed system. It has important practical application value and broad market prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 It is a flow chart of a distributed system optimization control method based on central cluster test management according to an embodiment of the present application;

[0064] Figure 2 is a flow chart of another distributed system optimization control method based on central cluster test management according to an embodiment of the present application;

[0065] Figure 3 is a structural diagram of a distributed system optimization control system based on central cluster test management according to an embodiment of the present application; and

[0066] Figure 4 It is a structural diagram of an electronic device according to a distributed system optimization control method based on central cluster test management according to an embodiment of the present application. DETAILED DESCRIPTION

[0067] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0068] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present application described here. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0069] In addition, the terms "installed", "set", "provided with", "connected", "connected", and "socketed" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral structure; it can be a mechanical connection or an electrical connection; it can be a direct connection, or an indirect connection through an intermediate medium, or it can be an internal connection between two devices, elements, or components. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0070] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0071] like Figure 1-2 As shown, according to an embodiment of the present invention, a distributed system optimization control method based on central cluster test management is provided, and the method includes the following steps S101 to S103:

[0072] Step S101, receiving registration information, initial state information and capability parameter information of each distributed system node;

[0073] It is possible to receive the registration information, initial status information and capability parameter information of each distributed system node, thereby providing a data basis for subsequent processing or calculation.

[0074] According to an embodiment of the present invention, preferably, receiving registration information, initial state information and capability parameter information of each distributed system node includes:

[0075] When registering, a compute node reports its current CPU usage and the number of tasks being executed, as well as its CPU model, number of cores, and the maximum number of concurrent tasks it can carry as its initial state and capability parameters;

[0076] Storage nodes report the usage of their storage space and the amount of data currently stored, and provide total storage capacity, read and write speeds, and supported storage protocols to describe their capabilities;

[0077] The network node reports the current network traffic and number of connections, as well as the maximum throughput, supported network protocols and latency performance to summarize its network processing capabilities;

[0078] The service node reports the current operating status and service response time of the service, as well as the type of service that can be provided, concurrent processing capabilities, and software and hardware environment.

[0079] Step S102: establishing a basic communication network through a cross-domain communication bridge according to the registration information of each distributed system node;

[0080] It can achieve good communication network connection effect, thus ensuring stable data transmission and interaction effect.

[0081] According to an embodiment of the present invention, preferably, a basic communication network is established through a cross-domain communication bridge according to registration information of each distributed system node, including:

[0082] After receiving the registration information of each distributed system node, analyzing the network configuration and capability parameters of each node; wherein the network configuration includes: IP address, port number and supported network protocol;

[0083] Based on the analysis results, determine the topology of the network; wherein the topology includes: the connection mode between nodes, the data transmission path and the routing strategy;

[0084] Configure cross-domain communication bridges, set bridging rules and data forwarding strategies;

[0085] Sending a network configuration instruction to each distributed system node through a cross-domain communication bridge; wherein the network configuration instruction includes: a specified IP address, a port number, a network protocol, and authentication information;

[0086] Each distributed system node adjusts its network settings according to the received network configuration instructions and completes the connection and registration with the cross-domain communication bridge;

[0087] After the establishment of the basic communication network is completed, communication testing is carried out through the cross-domain communication bridge to verify the connectivity, stability and performance indicators of the network.

[0088] Step S103: Send a performance data collection request to each registered distributed system node according to a preset time.

[0089] It can achieve the effect of regularly collecting performance data of each distributed system node, thereby ensuring accurate data collection results.

[0090] Step S104: Receive and analyze performance data from each distributed system node, and evaluate the health status and performance status of the entire distributed system based on the analysis results.

[0091] It can realize real-time analysis and evaluation of the performance data sent by each distributed system node, so as to obtain accurate health status and performance status of the entire distributed system, and provide guarantee for issuing precise control instructions.

[0092] According to an embodiment of the present invention, preferably, receiving and analyzing performance data from each distributed system node, and evaluating the health status and performance status of the entire distributed system according to the analysis results, includes:

[0093] Receive and analyze performance data from each distributed system node, wherein the performance data includes: CPU usage C, memory usage M, disk I / O rate S, network throughput D;

[0094] The normal operation thresholds of each performance indicator are predefined as follows: CPU usage does not exceed α, memory usage does not exceed β, disk I / O rate is lower than χ per second, and network throughput reaches at least φ;

[0095] The calculation formula of health score HS is:

[0096]

[0097]

[0098]

[0099]

[0100]

[0101] Among them, α, β, χ, and φ represent thresholds.

[0102] Step S105: Identify the distributed system nodes that need to be optimized or adjusted based on the evaluation results, and formulate corresponding optimization strategies;

[0103] It is possible to formulate corresponding distributed system node optimization strategies, thereby achieving good system optimization effects.

[0104] According to an embodiment of the present invention, preferably, based on the evaluation results, the distributed system nodes that need to be optimized or adjusted are identified, and corresponding optimization strategies are formulated, including:

[0105] When the CPU usage exceeds α and HS is less than 1, the computing node is downgraded;

[0106] When the memory usage exceeds β and HS is less than 1, the storage node is downgraded;

[0107] When the disk I / O rate exceeds χ and HS is less than 1, the storage node is downgraded;

[0108] When the network throughput is lower than φ and HS is less than 1, the network nodes are increased.

[0109] Step S106: convert the optimization strategy into specific execution instructions, and send them to the corresponding distributed system nodes to guide the system nodes to perform self-optimization and adjustment.

[0110] It can achieve good command control effect, thus achieving good guidance effect, and then enable the distributed system nodes to perform self-optimization and adjustment.

[0111] The present invention proposes a distributed system optimization control method based on central cluster test management. The method not only includes real-time performance monitoring and data analysis of distributed system nodes, but also covers system optimization decision-making and execution based on performance data, aiming to comprehensively improve the performance and stability of distributed systems. By defining specific performance monitoring indicators, optimization rules and health status assessment mechanisms, in-depth management and optimization of distributed systems can be achieved.

[0112] This application collects and analyzes the performance data of each node of the distributed system in real time, evaluates the health status of the system, and formulates and executes optimization strategies based on the data analysis results; and the central cluster test management platform adopted by the present invention can not only effectively improve the overall performance and stability of the distributed system, but also optimize resource allocation and reduce the workload of system management and maintenance. Through this method, the present invention aims to meet the requirements of efficient and reliable distributed system operation, and is particularly suitable for data centers, cloud computing platforms and IT infrastructure management of large enterprises, with significant practical application value and broad market prospects.

[0113] This application aims to achieve real-time performance monitoring, comprehensive data analysis, intelligent optimization decision-making and automated execution control of each node in the distributed system through an integrated Central Cluster Test Management Platform (CCTMP), thereby improving the performance and stability of the entire system, optimizing resource allocation and simplifying system management.

[0114] From the above description, it can be seen that the present application achieves the following technical effects:

[0115] In an embodiment of the present application, a distributed system optimization control method based on central cluster test management is adopted, by receiving registration information, initial state information and capability parameter information of each distributed system node; establishing a basic communication network through a cross-domain communication bridge according to the registration information of each distributed system node; issuing a performance data collection request to each registered distributed system node at a preset time; receiving and analyzing performance data from each distributed system node, and evaluating the health status and performance status of the entire distributed system based on the analysis results; identifying distributed system nodes that need to be optimized or adjusted based on the evaluation results, and formulating corresponding optimization strategies; converting the optimization strategies into specific execution instructions, sending them to the corresponding distributed system nodes, and guiding the system nodes to perform self-optimization and adjustment, achieving the purpose of supporting dynamic optimization and adaptive adjustment, thereby realizing the technical effect of improving system performance and stability, and further solving the problems in the existing technology that the distributed system still has deficiencies in real-time monitoring and comprehensive optimization of system performance, and the management system of the edge device cluster mainly focuses on the management of edge devices, and does not fully solve the technical problems of the performance optimization requirements of the distributed system as a whole.

[0116] According to an embodiment of the present invention, preferably, before receiving the registration information, initial state information and capability parameter information of each distributed system node, the method further includes:

[0117] Initialize the central cluster test management platform.

[0118] According to an embodiment of the present invention, preferably, the central cluster test management platform includes: the IP address and port number of each distributed system node, the hardware configuration of each node, the software environment, predefined performance monitoring indicators and warning thresholds.

[0119] Specifically, the hardware configuration of each node includes but is not limited to: CPU model, memory size; the software environment includes but is not limited to: operating system version, running services and applications.

[0120] According to an embodiment of the present invention, preferably, initializing the central cluster test management platform includes:

[0121] Installation and deployment of software, loading of configuration files, startup of necessary services and initial status check. The startup of necessary services includes but is not limited to: database services, network communication services, and data analysis services.

[0122] like Figure 3 As shown, in order to achieve the above purpose, according to another aspect of the present application, a distributed system optimization control system based on central cluster test management is provided. The distributed system optimization control system based on central cluster test management includes:

[0123] The receiving module 301 is used to receive the registration information, initial state information and capability parameter information of each distributed system node;

[0124] It is possible to receive the registration information, initial status information and capability parameter information of each distributed system node, thereby providing a data basis for subsequent processing or calculation.

[0125] A basic communication network establishment module 302 is used to establish a basic communication network through a cross-domain communication bridge according to the registration information of each distributed system node;

[0126] It can achieve good communication network connection effect, thus ensuring stable data transmission and interaction effect.

[0127] The performance data collection request module 303 is used to send a performance data collection request to each registered distributed system node according to a preset time;

[0128] It can achieve the effect of regularly collecting performance data of each distributed system node, thereby ensuring accurate data collection results.

[0129] An analysis and evaluation module 304 is used to receive and analyze performance data from each distributed system node, and evaluate the health status and performance status of the entire distributed system based on the analysis results;

[0130] It can realize real-time analysis and evaluation of the performance data sent by each distributed system node, so as to obtain accurate health status and performance status of the entire distributed system, and provide guarantee for issuing precise control instructions.

[0131] Identify and formulate optimization strategy module 305, for identifying distributed system nodes that need to be optimized or adjusted based on the evaluation results, and formulate corresponding optimization strategies;

[0132] It is possible to formulate corresponding distributed system node optimization strategies, thereby achieving good system optimization effects.

[0133] The sending guidance module 306 is used to convert the optimization strategy into specific execution instructions, and send them to the corresponding distributed system nodes to guide the system nodes to perform self-optimization and adjustment.

[0134] It can achieve good command control effect, thus achieving good guidance effect, and then enable the distributed system nodes to perform self-optimization and adjustment.

[0135] From the above description, it can be seen that the present application achieves the following technical effects:

[0136] In an embodiment of the present application, a distributed system optimization control method based on central cluster test management is adopted, by receiving registration information, initial state information and capability parameter information of each distributed system node; establishing a basic communication network through a cross-domain communication bridge according to the registration information of each distributed system node; issuing a performance data collection request to each registered distributed system node at a preset time; receiving and analyzing performance data from each distributed system node, and evaluating the health status and performance status of the entire distributed system based on the analysis results; identifying distributed system nodes that need to be optimized or adjusted based on the evaluation results, and formulating corresponding optimization strategies; converting the optimization strategies into specific execution instructions, sending them to the corresponding distributed system nodes, and guiding the system nodes to perform self-optimization and adjustment, achieving the purpose of supporting dynamic optimization and adaptive adjustment, thereby realizing the technical effect of improving system performance and stability, and further solving the problems in the existing technology that the distributed system still has deficiencies in real-time monitoring and comprehensive optimization of system performance, and the management system of the edge device cluster mainly focuses on the management of edge devices, and does not fully solve the technical problems of the performance optimization requirements of the distributed system as a whole.

[0137] Specifically, further explanation is given by the following examples;

[0138] Embodiment 1:

[0139] like Figure 1 As shown, this embodiment presupposes a distributed computing environment, which is composed of multiple computing nodes, storage nodes and network nodes, for processing large-scale data analysis tasks. The system integrates a distributed system optimization control platform (CCTMP) based on central cluster test management, which is designed to monitor and optimize the performance of the entire distributed system.

[0140] S1: Initialization phase: The Central Cluster Test Management Platform (CCTMP) starts and loads the system configuration, including node information, performance monitoring indicators, and optimization rules. Distributed nodes (computing, storage, and network nodes) register with the CCTMP and report their initial status and capability parameters.

[0141] S2: Performance monitoring phase: CCTMP periodically sends performance data collection requests to distributed nodes. Compute nodes report CPU and memory usage, storage nodes report disk I / O rate and usage, and network nodes report network throughput and latency.

[0142] S3: Data analysis and decision-making stage: The performance data collected by CCTMP is processed by the data analysis and decision-making engine. The engine uses predefined algorithms (such as the aforementioned health score HS calculation) to analyze the data and identify performance bottlenecks or optimization opportunities.

[0143] S4: Optimization execution phase: Based on the analysis results, CCTMP formulates optimization strategies and sends optimization instructions to the corresponding distributed nodes. Distributed nodes perform specific optimization operations based on the received instructions, such as adjusting resource allocation, changing task scheduling strategies, etc.

[0144] In this simulation scenario, assume that CCTMP detects that the CPU usage of a computing node continues to exceed a predetermined threshold (e.g., 70%) during the performance monitoring phase, indicating that the node may be overloaded. The data analysis and decision engine then analyzes the performance data of the node and other nodes in the system to determine whether it is necessary to reallocate tasks or adjust resource allocation to reduce the load on the node.

[0145] Based on the analysis results of the decision engine, CCTMP sends optimization instructions to the computing node, which may include migrating some computing tasks to nodes with lighter loads. At the same time, CCTMP may also send instructions to related storage nodes and network nodes to optimize data access paths and network communication strategies to support the migration of computing tasks and the overall performance optimization of distributed systems.

[0146] After a series of optimization operations, the CPU usage of the computing node was successfully reduced to a reasonable range, and the performance and stability of the entire distributed system were significantly improved. In addition, CCTMP continues to monitor system performance to ensure that the system remains in the optimal state for a long time.

[0147] Through this simulation scenario, the present invention demonstrates the working mode and interaction of each module in the present invention in practical application. The present invention provides an effective method that can not only monitor and analyze the performance of a distributed system in real time, but also dynamically adjust the optimization strategy according to actual conditions to achieve continuous optimization of system performance. This method is applicable to various distributed computing environments, especially for scenarios that process large-scale data analysis tasks, and can significantly improve the processing power and stability of the system.

[0148] like Figure 4 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, ROM 12 and RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0149] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0150] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The processor 11 executes the various methods and processes described above, such as a distributed system optimization control method based on central cluster test management.

[0151] In some embodiments, the distributed system optimization control method based on central cluster test management can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 10 via ROM12 and / or communication unit 19. When the computer program is loaded into RAM13 and executed by processor 11, one or more steps of the distributed system optimization control method based on central cluster test management described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to execute the distributed system optimization control method based on central cluster test management by any other appropriate means (for example, by means of firmware).

[0152] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0153] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0154] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, 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 of the foregoing.

[0155] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0156] The systems and techniques described herein may be implemented in a computing system that includes a backend component (e.g., as a data server), or a computing system that includes a middleware component (e.g., an application server), or a computing system that includes a frontend component (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LA), a wide area network (WA), a blockchain network, and the Internet.

[0157] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0158] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0159] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A distributed system optimization control method based on central cluster test management, characterized in that: The following steps are involved: Receive registration information, initial status information and capability parameter information of each distributed system node; Establish a basic communication network through a cross-domain communication bridge based on the registration information of each distributed system node; Sending a performance data collection request to each registered distributed system node at a preset time; Receive and analyze performance data from each distributed system node, and evaluate the health and performance status of the entire distributed system based on the analysis results; Based on the evaluation results, identify the distributed system nodes that need to be optimized or adjusted, and formulate corresponding optimization strategies; The optimization strategy is converted into specific execution instructions and sent to the corresponding distributed system nodes to guide the system nodes to perform self-optimization and adjustment.

2. The distributed system optimization control method based on central cluster test management according to claim 1 is characterized in that: Before receiving the registration information, initial status information and capability parameter information of each distributed system node, it also includes: Initialize the central cluster test management platform.

3. The distributed system optimization control method based on central cluster test management according to claim 2 is characterized in that: Central cluster test management platform, including: The IP address and port number of each distributed system node, the hardware configuration of each node, the software environment, predefined performance monitoring indicators and warning thresholds.

4. The distributed system optimization control method based on central cluster test management according to claim 2 is characterized in that: Initialize the central cluster test management platform, including: Installation and deployment of software, loading of configuration files, startup of necessary services and initial status check.

5. The distributed system optimization control method based on central cluster test management according to claim 1, characterized in that: Receive registration information, initial status information, and capability parameter information of each distributed system node, including: When registering, a compute node reports its current CPU usage and the number of tasks being executed, as well as its CPU model, number of cores, and the maximum number of concurrent tasks it can carry as its initial state and capability parameters; Storage nodes report the usage of their storage space and the amount of data currently stored, and provide total storage capacity, read and write speeds, and supported storage protocols to describe their capabilities; The network node reports the current network traffic and number of connections, as well as the maximum throughput, supported network protocols and latency performance to summarize its network processing capabilities; The service node reports the current operating status and service response time of the service, as well as the type of service that can be provided, concurrent processing capabilities, and software and hardware environment.

6. The distributed system optimization control method based on central cluster test management according to claim 1, characterized in that: According to the registration information of each distributed system node, a basic communication network is established through a cross-domain communication bridge, including: After receiving the registration information of each distributed system node, analyzing the network configuration and capability parameters of each node; wherein the network configuration includes: IP address, port number and supported network protocol; Based on the analysis results, determine the topology of the network; wherein the topology includes: the connection mode between nodes, the data transmission path and the routing strategy; Configure cross-domain communication bridges, set bridging rules and data forwarding strategies; Sending a network configuration instruction to each distributed system node through a cross-domain communication bridge; wherein the network configuration instruction includes: a specified IP address, a port number, a network protocol, and authentication information; Each distributed system node adjusts its network settings according to the received network configuration instructions and completes the connection and registration with the cross-domain communication bridge; After the establishment of the basic communication network is completed, communication testing is carried out through the cross-domain communication bridge to verify the connectivity, stability and performance indicators of the network.

7. The distributed system optimization control method based on central cluster test management according to claim 1, characterized in that: Receive and analyze performance data from each distributed system node, and evaluate the health and performance of the entire distributed system based on the analysis results, including: Receive and analyze performance data from each distributed system node, wherein the performance data includes: CPU usage C, memory usage M, disk I / O rate S, network throughput D; The normal operation thresholds of each performance indicator are predefined as follows: CPU usage does not exceed α, memory usage does not exceed β, disk I / O rate is lower than χ per second, and network throughput reaches at least φ; The calculation formula of health score HS is: Among them, α, β, χ, and φ represent thresholds.

8. The distributed system optimization control method based on central cluster test management according to claim 1, characterized in that: Based on the evaluation results, the distributed system nodes that need to be optimized or adjusted are identified, and corresponding optimization strategies are formulated, including: When the CPU usage exceeds α and HS is less than 1, the computing node is downgraded; When the memory usage exceeds β and HS is less than 1, the storage node is downgraded; When the disk I / O rate exceeds χ and HS is less than 1, the storage node is downgraded; When the network throughput is lower than φ and HS is less than 1, the network nodes are adjusted upward.

9. Distributed system optimization control system based on central cluster test management, characterized in that: include: A receiving module, used to receive registration information, initial status information and capability parameter information of each distributed system node; Establishing a basic communication network module, which is used to establish a basic communication network through a cross-domain communication bridge according to the registration information of each distributed system node; A performance data collection request module is used to send a performance data collection request to each registered distributed system node according to a preset time; The analysis and evaluation module is used to receive and analyze the performance data from each distributed system node, and evaluate the health status and performance status of the entire distributed system based on the analysis results; Identify and formulate optimization strategy module, which is used to identify the distributed system nodes that need to be optimized or adjusted based on the evaluation results, and formulate corresponding optimization strategies; The sending guidance module is used to convert the optimization strategy into specific execution instructions, which are sent to the corresponding distributed system nodes to guide the system nodes to perform self-optimization and adjustment.

10. An electronic device, characterized in that The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the distributed system optimization control method based on central cluster test management as described in any one of claims 1-8.

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