Performance optimization method of distributed account book system

Abstract

The invention belongs to the technical field of distributed account books, and particularly relates to a performance optimization method of a distributed account book system, which comprises the following steps: step 1, node architecture optimization: improving the processing capacity, memory and storage of nodes, reasonably configuring the load of the nodes, and avoiding overload of some nodes; and step 2, consensus algorithm improvement: the workload proof is converted to the right proof or other more efficient consensus mechanism, and the communication complexity and the calculation amount in the consensus process are reduced. According to the distributed account book system, the performance, the efficiency and the safety of the distributed account book system can be comprehensively improved by improving the node performance, improving the consensus algorithm, optimizing the transaction processing and the network layer, saving the storage space, improving the intelligent contract, simplifying the protocol layer and considering the safety and the performance balance at the same time, and the more efficient and reliable distributed account book system is provided for users.

Description

Technical Field

[0001] The present invention belongs to the technical field of distributed ledgers, and in particular relates to a performance optimization method for a distributed ledger system. Background Art

[0002] The distributed ledger system is an advanced data management technology that manages and maintains transaction records by distributing and storing ledger data on multiple network nodes. Unlike traditional centralized systems, the distributed ledger system manages data in a decentralized manner, and each node maintains a complete copy of the ledger, thereby improving the transparency and tamper resistance of the system. The system ensures the consistency of ledger data among all nodes through distributed consensus algorithms (such as proof of work, proof of stake, etc.), and uses encryption technology to ensure data security and prevent unauthorized access and data tampering. In addition, since data is redundantly stored on multiple nodes, the system has high availability and fault tolerance, and the system can still operate normally even if some nodes fail. The transparency of the distributed ledger system allows all transaction records to be viewed and verified by all nodes, thereby improving the credibility and auditability of the data. This system is widely used in financial services (such as cryptocurrency, payment settlement, cross-border remittances), supply chain management (for tracking and verifying the flow of goods in the supply chain), smart contracts (automatically executing contract terms), identity authentication (verifying user identity) and medical records (managing and sharing medical information). It provides a safe, reliable and efficient data management solution that meets the high requirements of modern society for data management and transparency.

[0003] The node performance of the existing distributed ledger system is not well optimized. The computational workload of each node is large, and the system response speed and data transmission efficiency are poor, making it difficult to balance security and performance at the same time. Therefore, we propose a performance optimization method for distributed ledger systems to solve the above problems. Summary of the invention

[0004] The purpose of the present invention is to provide a performance optimization method for a distributed ledger system, which can improve node performance, improve consensus algorithms, optimize transaction processing and network layers, save storage space, improve smart contracts, simplify protocol layers, and balance security and performance. It can comprehensively improve the performance, efficiency and security of the distributed ledger system and provide users with a more efficient and reliable distributed ledger system.

[0005] The technical solution adopted by the present invention is as follows:

[0006] A performance optimization method for a distributed ledger system, the performance optimization method comprising the following steps:

[0007] Step 1. Node architecture optimization: Improve the processing power, memory and storage of nodes, reasonably configure the load of nodes, and avoid overloading of some nodes;

[0008] Step 2. Consensus algorithm improvement: switch from proof of work to proof of stake or other more efficient consensus mechanisms to reduce the communication complexity and computational complexity in the consensus process;

[0009] Step 3. Transaction processing optimization: Bundle multiple transactions to reduce transaction processing overhead and optimize transaction data verification and dissemination mechanisms;

[0010] Step 4. Network layer optimization: adopt more efficient data transmission protocols, reduce network latency, optimize information propagation paths between nodes, and reduce network congestion;

[0011] Step 5. Storage optimization: Store some data off-chain, improve efficiency by combining off-chain data with on-chain status, compress the stored data, and reduce storage space;

[0012] Step 6. Smart contract optimization: write efficient smart contract code, reduce execution costs, optimize the logic of smart contracts, and reduce computational complexity and execution time;

[0013] Step 7. Protocol layer optimization: Optimize the design of the protocol layer, reduce protocol overhead and complexity, and design a protocol architecture that supports expansion to meet future performance requirements;

[0014] Step 8. Balance security and performance: Ensure system security while improving performance, and avoid security vulnerabilities caused by performance optimization;

[0015] Step 9. Monitor and adjust: Regularly monitor system performance, identify bottlenecks and problems, and dynamically adjust system parameters based on actual operating conditions to maintain optimal performance.

[0016] In a preferred embodiment, the node architecture optimization also includes using monitoring tools to evaluate the current performance of the node. The monitoring tools include CPU, memory, disk I / O, and network traffic monitoring, selecting a higher performance CPU according to system requirements, increasing RAM capacity, monitoring the node load in real time, identifying which nodes or parts have higher loads, determining the maximum processing capacity of each node, and recording benchmark performance data. Different roles and loads are assigned according to the node's capabilities and task types, a dynamic load balancing mechanism is designed, node task allocation is adjusted according to real-time load conditions, and a load balancer is set to distribute traffic.

[0017] In a preferred solution, the consensus algorithm improvement also includes analyzing the performance of the current consensus algorithm, including throughput, latency, and resource consumption, evaluating whether a more efficient consensus algorithm is needed based on the system's transaction speed, security, and degree of decentralization, evaluating the applicability of PoS, and designing a detailed plan for the consensus mechanism, including the algorithm's workflow, node roles, and reward mechanism. Conducting simulation tests and performance evaluations to verify whether the new consensus algorithm meets system requirements, analyzing the communication complexity, computational complexity, and latency of the current consensus protocol, identifying possible performance bottlenecks in the protocol, optimizing the protocol, reducing the number of message transmissions between nodes, and reducing the computational complexity of each node through algorithm optimization.

[0018] In a preferred solution, the transaction processing optimization also includes evaluating the current transaction volume and processing flow in the system, identifying bottlenecks in transaction processing, analyzing the overhead and time consumption of single transaction processing, defining batch data formats, merging similar or related transactions, adjusting transaction processing modules to enable them to receive and process batch transactions, optimizing the storage method of transaction data to support batch writing and reading, gradually deploying batch processing mechanisms into production environments, setting up monitoring tools, tracking performance indicators of batch processing, optimizing transaction verification algorithms, and reducing computational complexity.

[0019] In a preferred embodiment, the network layer optimization also includes using network monitoring tools to measure the delay and bandwidth usage of data transmission, optimizing existing transmission protocols, including enabling protocol compression, adjusting flow control algorithms, optimizing header compression, compressing transmitted data to reduce the size of data transmission, dynamically adjusting the compression rate according to network status to reduce delays while ensuring transmission efficiency, setting up caches at the edge or intermediate nodes of the network to reduce repeated data transmission, and using CDN to distribute data to nodes closer to users to reduce transmission delays.

[0020] In a preferred solution, the storage optimization also includes analyzing the data types, data volumes and storage requirements in the existing system, identifying which data are suitable for off-chain storage, evaluating the current on-chain storage bottlenecks, including insufficient storage space or slow storage read / write speeds, determining which data can be stored off-chain, including historical transaction data, log information, and large data files, designing an on-chain identification mechanism for tracking data stored off-chain, and designing a mechanism for synchronizing off-chain storage with on-chain status.

[0021] In a preferred embodiment, the smart contract optimization also includes code review of existing smart contracts, using gas consumption to analyze the execution cost and execution time of the contract, identifying high-overhead parts, simplifying the logical structure of the smart contract, minimizing the frequency of function calls, and inlining frequently called small functions into the main function to reduce calling overhead, simplifying calculation algorithms, optimizing complex mathematical operations, or moving complex operations to off-chain processing.

[0022] In a preferred solution, the protocol layer optimization also includes using tools to measure the protocol's latency, bandwidth occupancy, and computational complexity, identifying possible points for improvement, simplifying the message exchange process in the protocol, reducing the number of messages or merging message types, compressing data packets, reducing the size of data headers, using efficient data compression algorithms to reduce the size of messages, using Protobuf and MessagePack formats, and introducing parallel processing technology in the protocol processing process.

[0023] In a preferred embodiment, the security and performance balance also includes conducting a thorough security audit of existing systems, including code review, vulnerability scanning and security testing, selecting encryption algorithms in performance-sensitive operations, using symmetric encryption for encryption and decryption of large amounts of data, using efficient network transmission protocols, reducing message latency and packet size, deploying anomaly detection systems to identify any potential security threats, and configuring automated tools to continuously monitor possible weaknesses in the system.

[0024] In a preferred solution, the monitoring and adjustment also includes monitoring the health status of the system, including node status, storage usage, and database performance, deploying log management tools to collect and analyze system logs, configuring an alarm system, triggering an alarm when an indicator exceeds a preset threshold, notifying operation and maintenance personnel to handle it, regularly collecting performance data and system status information, updating the monitoring platform in real time, and determining optimization goals based on the monitoring results, including improving throughput, reducing latency, and reducing resource consumption, and performing parameter adjustments and performance optimization in a test environment.

[0025] The technical effects achieved by the present invention are:

[0026] By optimizing the node architecture, improving the processing power, memory and storage of the nodes, and reasonably configuring the load, the overall system performance can be significantly improved, and overloading of certain nodes can be avoided, thereby improving the system's response speed and processing power. By switching the consensus algorithm from proof of work to proof of stake or other more efficient mechanisms, the communication complexity and computational complexity in the consensus process can be reduced, transaction confirmation time can be shortened, energy consumption can be reduced, and the transaction throughput and efficiency of the system can be improved;

[0027] Packaging multiple transactions to reduce the processing overhead of a single transaction and optimizing the verification and propagation mechanism of transaction data can significantly improve the efficiency of transaction processing and the throughput of the system, and reduce transaction costs. By adopting a more efficient data transmission protocol, reducing network latency, and optimizing the information propagation path between nodes, the system's response speed and data transmission efficiency can be improved, and the performance impact caused by network congestion can be reduced. By storing part of the data off-chain and compressing the data, the storage space occupied can be effectively reduced, the storage efficiency can be improved, and the storage cost can be reduced at the same time.

[0028] Writing efficient smart contract code, reducing execution costs, and optimizing the logic of smart contracts can reduce computing power and execution time, improve the execution efficiency of smart contracts, reduce resource consumption, optimize protocol layer design, reduce protocol overhead and complexity, improve system processing efficiency, support future expansion needs, reduce resource consumption for protocol processing, ensure system security while optimizing performance, and avoid security vulnerabilities caused by performance optimization, thereby ensuring the overall security of the system and the integrity of data. By regularly monitoring system performance, identifying bottlenecks and problems, and dynamically adjusting system parameters according to actual operating conditions, the system can be kept in the best state, performance problems can be solved in a timely manner, and the stability and reliability of the system can be ensured. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 It is a schematic diagram of a performance optimization method of a distributed ledger system of the present invention. DETAILED DESCRIPTION

[0030] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0031] See also Figure 1 As shown, the present invention provides a performance optimization method for a distributed ledger system, and the performance optimization method comprises the following steps:

[0032] Step 1. Node architecture optimization: Improve the processing power, memory and storage of nodes, reasonably configure the load of nodes, and avoid overloading of some nodes;

[0033] Step 2. Consensus algorithm improvement: switch from proof of work to proof of stake or other more efficient consensus mechanisms to reduce the communication complexity and computational complexity in the consensus process;

[0034] Step 3. Transaction processing optimization: Bundle multiple transactions to reduce transaction processing overhead and optimize transaction data verification and dissemination mechanisms;

[0035] Step 4. Network layer optimization: adopt more efficient data transmission protocols, reduce network latency, optimize information propagation paths between nodes, and reduce network congestion;

[0036] Step 5. Storage optimization: Store some data off-chain, improve efficiency by combining off-chain data with on-chain status, compress the stored data, and reduce storage space;

[0037] Step 6. Smart contract optimization: write efficient smart contract code, reduce execution costs, optimize the logic of smart contracts, and reduce computational complexity and execution time;

[0038] Step 7. Protocol layer optimization: Optimize the design of the protocol layer, reduce protocol overhead and complexity, and design a protocol architecture that supports expansion to meet future performance requirements;

[0039] Step 8. Balance security and performance: Ensure system security while improving performance, and avoid security vulnerabilities caused by performance optimization;

[0040] Step 9. Monitor and adjust: Regularly monitor system performance, identify bottlenecks and problems, and dynamically adjust system parameters based on actual operating conditions to maintain optimal performance.

[0041] Node architecture optimization also includes using monitoring tools to evaluate the current performance of the node. The monitoring tools include CPU, memory, disk I / O, and network traffic monitoring. Select a higher-performance CPU based on system requirements, increase RAM capacity, monitor the node load in real time, identify which nodes or parts have higher loads, determine the maximum processing capacity of each node, and record benchmark performance data. Assign different roles and loads based on the node's capabilities and task types, design a dynamic load balancing mechanism, adjust node task allocation based on real-time load conditions, and set up a load balancer to distribute traffic.

[0042] Consensus algorithm improvements also include analyzing the performance of the current consensus algorithm, including throughput, latency, and resource consumption; evaluating whether a more efficient consensus algorithm is needed based on the system's transaction speed, security, and degree of decentralization; evaluating the applicability of PoS; and designing a detailed plan for the consensus mechanism, including the algorithm's workflow, node roles, and reward mechanism. Conducting simulation tests and performance evaluations to verify whether the new consensus algorithm meets system requirements; analyzing the communication complexity, computational complexity, and latency of the current consensus protocol; identifying possible performance bottlenecks in the protocol; optimizing the protocol; reducing the number of message transmissions between nodes; and reducing the computational complexity of each node through algorithm optimization.

[0043] Transaction processing optimization also includes evaluating the current transaction volume and processing flow in the system, identifying bottlenecks in transaction processing, analyzing the overhead and time consumption of single transaction processing, defining batch data formats, merging similar or related transactions, adjusting transaction processing modules so that they can receive and process batch transactions, optimizing the storage method of transaction data to support batch writing and reading, gradually deploying batch processing mechanisms into production environments, setting up monitoring tools, tracking performance indicators of batch processing, optimizing transaction verification algorithms, and reducing computational complexity.

[0044] Network layer optimization also includes using network monitoring tools to measure the latency and bandwidth usage of data transmission, optimizing existing transmission protocols, including enabling protocol compression, adjusting flow control algorithms, optimizing header compression, compressing transmitted data to reduce the size of data transmission, dynamically adjusting the compression rate according to network status to reduce latency while ensuring transmission efficiency, setting up caches at the edge or intermediate nodes of the network to reduce repeated data transmission, and using CDN to distribute data to nodes closer to users to reduce transmission latency.

[0045] Storage optimization also includes analyzing the data types, data volumes, and storage requirements in existing systems, identifying which data is suitable for off-chain storage, evaluating current on-chain storage bottlenecks, including insufficient storage space or slow storage read / write speeds, determining which data can be stored off-chain, including historical transaction data, log information, and large data files, designing an on-chain identification mechanism to track data stored off-chain, and designing a mechanism for synchronizing off-chain storage with on-chain status.

[0046] Smart contract optimization also includes code review of existing smart contracts, using gas consumption to analyze the execution cost and execution time of the contract, identifying high-overhead parts, simplifying the logical structure of the smart contract, minimizing the frequency of function calls, and inlining frequently called small functions into the main function to reduce calling overhead, simplifying calculation algorithms, optimizing complex mathematical operations, or moving complex operations to off-chain processing.

[0047] Protocol layer optimization also includes using tools to measure the protocol's latency, bandwidth usage, and computational complexity, identifying possible points for improvement, simplifying the message exchange process in the protocol, reducing the number of messages or merging message types, compressing data packets, reducing the size of data headers, using efficient data compression algorithms to reduce message size, using Protobuf and MessagePack formats, and introducing parallel processing technology in the protocol processing process.

[0048] Balancing security and performance also includes conducting a thorough security audit of existing systems, including code review, vulnerability scanning, and security testing, selecting encryption algorithms in performance-sensitive operations, using symmetric encryption for encryption and decryption of large amounts of data, using efficient network transmission protocols, reducing message latency and packet size, deploying anomaly detection systems to identify any potential security threats, and configuring automated tools to continuously monitor possible weaknesses in the system.

[0049] Monitoring and adjustment also include monitoring the health status of the system, including node status, storage usage, and database performance; deploying log management tools to collect and analyze system logs; configuring an alarm system to trigger an alarm when an indicator exceeds a preset threshold and notify operation and maintenance personnel to handle it; regularly collecting performance data and system status information; updating the monitoring platform in real time; and determining optimization goals based on monitoring results, including increasing throughput, reducing latency, and reducing resource consumption; and performing parameter adjustments and performance optimization in a test environment.

[0050] In the present invention, by optimizing the node architecture, improving the processing power, memory and storage of the nodes, and reasonably configuring the load, the overall performance of the system can be significantly improved, overloading of certain nodes can be avoided, thereby improving the response speed and processing power of the system, and shifting the consensus algorithm from proof of work to proof of stake or other more efficient mechanisms, which can reduce the communication complexity and computational complexity in the consensus process, shorten the transaction confirmation time, reduce energy consumption, and improve the transaction throughput and efficiency of the system;

[0051] Packaging multiple transactions to reduce the processing overhead of a single transaction and optimizing the verification and propagation mechanism of transaction data can significantly improve the efficiency of transaction processing and the throughput of the system, and reduce transaction costs. By adopting a more efficient data transmission protocol, reducing network latency, and optimizing the information propagation path between nodes, the system's response speed and data transmission efficiency can be improved, and the performance impact caused by network congestion can be reduced. By storing part of the data off-chain and compressing the data, the storage space occupied can be effectively reduced, the storage efficiency can be improved, and the storage cost can be reduced at the same time.

[0052] Writing efficient smart contract code, reducing execution costs, and optimizing the logic of smart contracts can reduce computing power and execution time, improve the execution efficiency of smart contracts, reduce resource consumption, optimize protocol layer design, reduce protocol overhead and complexity, improve system processing efficiency, support future expansion needs, reduce resource consumption for protocol processing, ensure system security while optimizing performance, and avoid security vulnerabilities caused by performance optimization, thereby ensuring the overall security of the system and the integrity of data. By regularly monitoring system performance, identifying bottlenecks and problems, and dynamically adjusting system parameters according to actual operating conditions, the system can be kept in the best state, performance problems can be solved in a timely manner, and the stability and reliability of the system can be ensured.

[0053] The above is only a preferred embodiment of the present invention. It should be noted that, for those skilled in the art, several improvements and modifications can be made without departing from the principles of the present invention, and these improvements and modifications should also be considered as the protection scope of the present invention. The structures, devices and operating methods not specifically described and explained in the present invention shall be implemented according to the conventional means in the art unless otherwise specified and limited.

Claims

1. A method for optimizing the performance of a distributed ledger system, characterized in that: The performance optimization method comprises the following steps: Step 1. Node architecture optimization: Improve the processing power, memory and storage of nodes, reasonably configure the load of nodes, and avoid overloading of some nodes; Step 2. Consensus algorithm improvement: switch from proof of work to proof of stake or other more efficient consensus mechanisms to reduce the communication complexity and computational complexity in the consensus process; Step 3. Transaction processing optimization: Bundle multiple transactions to reduce transaction processing overhead and optimize transaction data verification and dissemination mechanisms; Step 4. Network layer optimization: adopt more efficient data transmission protocols, reduce network latency, optimize information propagation paths between nodes, and reduce network congestion; Step 5. Storage optimization: Store some data off-chain, improve efficiency by combining off-chain data with on-chain status, compress the stored data, and reduce storage space; Step 6. Smart contract optimization: write efficient smart contract code, reduce execution costs, optimize the logic of smart contracts, and reduce computational complexity and execution time; Step 7. Protocol layer optimization: Optimize the design of the protocol layer, reduce protocol overhead and complexity, and design a protocol architecture that supports expansion to meet future performance requirements; Step 8. Balance security and performance: Ensure system security while improving performance, and avoid security vulnerabilities caused by performance optimization; Step 9. Monitor and adjust: Regularly monitor system performance, identify bottlenecks and problems, and dynamically adjust system parameters based on actual operating conditions to maintain optimal performance.

2. The performance optimization method of a distributed ledger system according to claim 1, characterized in that: The node architecture optimization also includes using monitoring tools to evaluate the current performance of the node. The monitoring tools include CPU, memory, disk I / O, and network traffic monitoring, selecting a higher performance CPU based on system requirements, increasing RAM capacity, monitoring the node load in real time, identifying which nodes or parts have higher loads, determining the maximum processing capacity of each node, and recording benchmark performance data, allocating different roles and loads based on the node's capabilities and task types, designing a dynamic load balancing mechanism, adjusting node task allocation based on real-time load conditions, and setting a load balancer to distribute traffic.

3. The performance optimization method of a distributed ledger system according to claim 1, characterized in that: The consensus algorithm improvement also includes analyzing the performance of the current consensus algorithm, including throughput, latency, and resource consumption; evaluating whether a more efficient consensus algorithm is needed based on the system's transaction speed, security, and degree of decentralization; evaluating the applicability of PoS; and designing a detailed plan for the consensus mechanism, including the algorithm's workflow, node roles, and reward mechanism. Conducting simulation tests and performance evaluations to verify whether the new consensus algorithm meets system requirements; analyzing the communication complexity, computational complexity, and latency of the current consensus protocol; identifying possible performance bottlenecks in the protocol; optimizing the protocol; reducing the number of message transmissions between nodes; and reducing the computational complexity of each node through algorithm optimization.

4. The performance optimization method of a distributed ledger system according to claim 1, characterized in that: The transaction processing optimization also includes evaluating the current transaction volume and processing flow in the system, identifying bottlenecks in transaction processing, analyzing the overhead and time consumption of single transaction processing, defining batch data formats, merging similar or related transactions, adjusting transaction processing modules to enable them to receive and process batch transactions, optimizing the storage method of transaction data to support batch writing and reading, gradually deploying batch processing mechanisms into production environments, setting up monitoring tools, tracking performance indicators of batch processing, optimizing transaction verification algorithms, and reducing computational complexity.

5. The performance optimization method of a distributed ledger system according to claim 1, characterized in that: The network layer optimization also includes using network monitoring tools to measure the delay and bandwidth usage of data transmission, optimizing existing transmission protocols, including enabling protocol compression, adjusting flow control algorithms, optimizing header compression, compressing transmitted data to reduce the size of data transmission, dynamically adjusting the compression rate according to network status to reduce delays while ensuring transmission efficiency, setting up caches at the edge or intermediate nodes of the network to reduce repeated data transmission, and using CDN to distribute data to nodes closer to users to reduce transmission delays.

6. The performance optimization method of a distributed ledger system according to claim 1, characterized in that: The storage optimization also includes analyzing the data types, data volumes and storage requirements in the existing system, identifying which data are suitable for off-chain storage, evaluating the current on-chain storage bottlenecks, including insufficient storage space or slow storage read / write speeds, determining which data can be stored off-chain, including historical transaction data, log information, large data files, designing an on-chain identification mechanism for tracking data stored off-chain, and designing a mechanism for synchronizing off-chain storage with on-chain status.

7. The performance optimization method of a distributed ledger system according to claim 1, characterized in that: The smart contract optimization also includes code review of existing smart contracts, using Gas consumption to analyze the execution cost and execution time of the contract, identifying high-overhead parts, simplifying the logical structure of the smart contract, minimizing the frequency of function calls, and inlining frequently called small functions into the main function to reduce calling overhead, simplifying calculation algorithms, optimizing complex mathematical operations, or moving complex operations to off-chain processing.

8. The performance optimization method of a distributed ledger system according to claim 1, characterized in that: The protocol layer optimization also includes using tools to measure the protocol's latency, bandwidth usage, and computational complexity, identifying possible improvement points, simplifying the message exchange process in the protocol, reducing the number of messages or merging message types, compressing data packets, reducing the size of data headers, using efficient data compression algorithms to reduce message size, using Protobuf and MessagePack formats, and introducing parallel processing technology in the protocol processing process.

9. The performance optimization method of a distributed ledger system according to claim 1, characterized in that: The security and performance balance also includes conducting a thorough security audit of existing systems, including code review, vulnerability scanning and security testing, selecting encryption algorithms in performance-sensitive operations, using symmetric encryption for encryption and decryption of large amounts of data, using efficient network transmission protocols, reducing message latency and packet size, deploying anomaly detection systems to identify any potential security threats, and configuring automated tools to continuously monitor possible weaknesses in the system.

10. The performance optimization method of a distributed ledger system according to claim 1, characterized in that: The monitoring and adjustment also includes monitoring the health status of the system, including node status, storage usage, and database performance, deploying log management tools to collect and analyze system logs, configuring an alarm system, triggering an alarm when an indicator exceeds a preset threshold, notifying operation and maintenance personnel to handle it, regularly collecting performance data and system status information, and updating the monitoring platform in real time. According to the monitoring results, optimization goals are determined, including increasing throughput, reducing latency, and reducing resource consumption, and adjusting parameters and optimizing performance in a test environment.

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