Adaptive load balancing processing method and system based on blockchain network

Abstract

The present application provides an adaptive load balancing processing method and system based on a blockchain network, which can accurately analyze and pair key and derivative resource usage indicators by collecting the continuous load status characteristics of each blockchain node in the blockchain network, including multiple resource usage indicators. When encountering a unique resource usage tag and the current load balancing strategy does not cover the unique resource usage tag, if the derivative resource indicator is already in the strategy and the resource cluster associated with it contains other unique resource tags, an updated load balancing solution will be generated based on these resource usage indicator pairing sets to ensure that all unique resources are reasonably load balanced and regulated, thereby effectively improving the performance and stability of the blockchain network.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a method and system for adaptive load balancing processing based on a blockchain network. Background Art

[0002] With the widespread application of blockchain technology, the scale and complexity of blockchain networks are increasing. How to effectively manage and optimize the load balancing problem in blockchain networks has become a challenge that needs to be solved. Traditional load balancing methods are often based on centralized architectures and fixed resource allocation strategies, which are difficult to adapt to the decentralized and dynamic characteristics of blockchain networks.

[0003] In a blockchain network, each node is responsible for verifying, storing, and transmitting transaction data. The node load status directly affects the performance and stability of the entire network. Due to the distributed nature of the blockchain network, there may be large differences in the load status between nodes. Some nodes may be overloaded due to processing too many requests, while other nodes may be idle. This load imbalance will not only reduce the network's processing capacity, but may also increase transaction delays and failure rates, affecting user experience and the availability of the blockchain system.

[0004] In related technologies, the load status of each node in the blockchain network is usually monitored and analyzed, and the task allocation and resource usage of the nodes are dynamically adjusted to achieve load balancing. However, related technical solutions are mostly limited to simple load balancing algorithms, such as polling, random selection, etc., and lack in-depth analysis and precise matching of node load status characteristics. In addition, these solutions often ignore the unique resource usage tags that may exist in the blockchain network, and cannot effectively handle the load balancing problem of these special resources. Summary of the invention

[0005] In view of this, the purpose of this application is to provide an adaptive load balancing processing method and system based on a blockchain network.

[0006] According to the first aspect of the present application, a method for adaptive load balancing processing based on a blockchain network is provided, the method comprising:

[0007] Obtaining a load state feature distribution of each blockchain node among a plurality of blockchain nodes in a blockchain network, wherein the load state feature distribution includes a plurality of continuous load state features of each blockchain node, and the load state feature includes resource usage indicators of a plurality of resource usage tags;

[0008] Pairing each resource usage indicator covered by the load state feature to generate a pairing set of each resource usage indicator of the load state feature, wherein the resource usage indicator pairing set is a sequence of two resource usage indicators, the resource usage indicator pairing set includes a key resource usage indicator and a derived resource usage indicator, and the load balancing condition degree of the key resource usage indicator is greater than the load balancing condition degree of the derived resource usage indicator;

[0009] Obtain a load balancing control graph of the multiple blockchain nodes. If the key resource usage indicator is a unique resource usage tag, the recorded resource usage indicators of the load balancing control graph do not cover the key resource usage indicator, the recorded resource usage indicators include the derived resource usage indicators, and the first resource usage indicator cluster associated with the derived resource usage indicator in the load balancing control graph includes the resource usage indicator of the unique resource usage tag, then generate an updated load balancing scheme to the load balancing control graph based on the resource usage indicator pairing set, wherein the load balancing condition degree of the resource usage indicator of the unique resource usage tag is not less than the load balancing condition degree of the key resource usage indicator.

[0010] In a possible implementation of the first aspect, the method further includes:

[0011] If the key resource usage indicator is a unique resource usage label, the recorded resource usage indicator includes the key resource usage indicator, the recorded resource usage indicator includes the derived resource usage indicator, and the first resource usage indicator cluster includes resource usage indicators with unique resource usage labels, then the resource usage indicator pairing set is integrated into the second resource usage indicator cluster associated with the key resource usage indicator in the load balancing control diagram.

[0012] In a possible implementation of the first aspect, the method further includes:

[0013] If the key resource usage indicator is a unique resource usage tag, the recorded resource usage indicator includes the key resource usage indicator, the recorded resource usage indicator includes the derived resource usage indicator, and the first resource usage indicator cluster does not cover the resource usage indicator of the unique resource usage tag, then the resource usage indicator pairing set and the first resource usage indicator cluster are integrated into the second resource usage indicator cluster associated with the key resource usage indicator in the load balancing control diagram.

[0014] In a possible implementation of the first aspect, the method further includes:

[0015] If the key resource usage indicator is not a unique resource usage label, the recorded resource usage indicator includes the key resource usage indicator, and the recorded resource usage indicator includes the derived resource usage indicator, then the resource usage indicator pairing set and the second resource usage indicator cluster associated with the key resource usage indicator in the load balancing control diagram are integrated into the first resource usage indicator cluster.

[0016] In a possible implementation of the first aspect, the method further includes:

[0017] If the key resource usage indicator is a unique resource usage tag, the recorded resource usage indicators do not cover the key resource usage indicator, the recorded resource usage indicators include the derived resource usage indicators, and the first resource usage indicator cluster does not cover resource usage indicators of the unique resource usage tag, integrating the resource usage indicator pairing set into the first resource usage indicator cluster;

[0018] Alternatively, if the key resource usage indicator is not a unique resource usage tag, the recorded resource usage indicators do not cover the key resource usage indicator, and the recorded resource usage indicators include the derived resource usage indicator, the resource usage indicator pairing set is integrated into the first resource usage indicator cluster.

[0019] In a possible implementation of the first aspect, the method further includes:

[0020] If the recorded resource usage indicators include the key resource usage indicators and the recorded resource usage indicators do not cover the derived resource usage indicators, the resource usage indicator pairing set is integrated into a second resource usage indicator cluster associated with the key resource usage indicator in the load balancing control diagram.

[0021] In a possible implementation manner of the first aspect, pairing the resource usage indicators covered by the load state feature to generate a pairing set of resource usage indicators of the load state feature includes:

[0022] From the resource usage indicators covered by the load state characteristics, obtaining the resource usage indicator with the greatest load balancing condition as the key resource usage indicator;

[0023] From the resource usage indicators covered by the load state characteristics, obtaining a resource usage indicator whose load balancing condition is lower than the key resource usage indicator as a derived resource usage indicator;

[0024] Acquire a recording time domain from the load state characteristic;

[0025] The key resource usage indicator, the derived resource usage indicator and the recording time domain are aggregated to generate the resource usage indicator pairing set.

[0026] In a possible implementation of the first aspect, the resource usage indicator pairing set further includes a recording time domain, and the generating and updating the load balancing solution to the load balancing control graph according to the resource usage indicator pairing set includes:

[0027] Aggregating the key resource usage indicator with the recording time domain to generate a combined sequence of the key resource usage indicator;

[0028] Aggregating the derived resource usage indicator with the recording time domain to generate a combined sequence of the derived resource usage indicator;

[0029] generating the updated load balancing solution according to the key resource usage indicator and the derived resource usage indicator;

[0030] In the load balancing control graph, the combination sequence of the key resource usage indicators and the combination sequence of the derived resource usage indicators are loaded into the associated resource usage indicator cluster of the updated load balancing solution.

[0031] In a possible implementation manner of the first aspect, the step of generating the updated load balancing solution according to the key resource usage indicator and the derived resource usage indicator includes:

[0032] Quantitatively evaluate the key resource usage indicator and the derived resource usage indicator, analyze the weight, usage frequency, and correlation between the key resource usage indicator and the derived resource usage indicator in the load state characteristics, and other resource usage indicators to obtain an evaluation result;

[0033] Based on the evaluation results, predict the future resource requirements of each blockchain node, and based on the prediction results, calculate the amount of resources to be allocated to each blockchain node;

[0034] A task migration plan is generated according to the future resource demand and the amount of resources to be allocated, and the task migration plan is used as solution data in the updated load balancing solution.

[0035] According to the second aspect of the present application, a blockchain service system is provided, which includes a machine-readable storage medium and a processor, wherein the machine-readable storage medium stores machine-executable instructions, and when the processor executes the machine-executable instructions, the blockchain service system implements the aforementioned adaptive load balancing processing method based on the blockchain network.

[0036] According to the third aspect of the present application, a computer-readable storage medium is provided, in which computer-executable instructions are stored. When the computer-executable instructions are executed, the aforementioned adaptive load balancing processing method based on the blockchain network is implemented.

[0037] According to any one of the above aspects, the technical effect of the present application is:

[0038] By accurately acquiring and analyzing the load status characteristic distribution of each node in the blockchain network, we have achieved effective pairing of key resource usage indicators and derived resource usage indicators. This not only takes into account the real-time and continuity of resource usage indicators, but also significantly improves the load balancing capability of the blockchain network by identifying unique resource usage tags and performing targeted load balancing regulation.

[0039] Specifically, by real-time monitoring and analyzing the load status characteristic distribution of blockchain nodes, it is possible to timely discover and handle load imbalances, effectively avoiding the problem of network performance degradation caused by uneven resource allocation. The resource usage indicators are paired, especially the key resource usage indicators and the derivative resource usage indicators are distinguished, so that the formulation of the load balancing strategy is more accurate and targeted. This resource pairing method can more accurately reflect the actual usage of node resources, thereby improving the effect of load balancing. In addition, the role of unique resource usage labels in load balancing is particularly considered. By incorporating these special resources into the load balancing control diagram and generating and updating the load balancing scheme in a targeted manner, it is ensured that these key resources can be reasonably allocated and used. This not only improves the utilization rate of resources, but also enhances the stability and reliability of the network. In addition, the embodiment of the present application can dynamically adjust the load balancing strategy according to the real-time load status of the blockchain network, realizing efficient management and optimization of the network load. This adaptive control capability enables the present invention to adapt to blockchain networks of different scales and structures, and has wide applicability and scalability. Therefore, by accurately acquiring and analyzing the load status characteristic distribution of blockchain nodes, effective pairing of key resource usage indicators and derivative resource usage indicators is achieved, and load balancing regulation of unique resource usage tags is supported, which significantly improves the load balancing capability and network performance of the blockchain network. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other corresponding drawings can be obtained based on these drawings without paying creative work.

[0041] Figure 1A schematic diagram of a process flow of an adaptive load balancing processing method based on a blockchain network provided in an embodiment of the present application is shown;

[0042] Figure 2 A schematic diagram of the component structure of a blockchain service system for implementing the above-mentioned blockchain network-based adaptive load balancing processing method provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0043] The embodiments of the present application are described below in conjunction with the drawings in the present application. It should be understood that the implementation methods described below in conjunction with the drawings are exemplary descriptions for explaining the technical solutions of the embodiments of the present application and do not constitute a limitation on the technical solutions of the embodiments of the present application.

[0044] It will be understood by those skilled in the art that, unless specifically stated, the singular forms "one", "said", and "the" used herein may also include plural forms. It should be further understood that the terms "including" and "comprising" used in the embodiments of the present application refer to that the corresponding features can be implemented as the presented features, information, data, steps, operations, elements and / or components, but do not exclude the implementation as other features, information, data, steps, operations, elements, components and / or combinations thereof supported by the technical field. It should be understood that when an element is "connected" or "coupled" to another element, the element may be directly connected or coupled to the other element, or may refer to the element and the other element establishing a connection relationship through an intermediate element. In addition, the "connection" or "coupling" used herein may include wireless connection or wireless coupling, and the term "and / or" used herein indicates at least one of the items defined by the term, such as "A and / or B" may be implemented as "A", or as "B", or as "A and B".

[0045] In order to make the purpose, technical solution and advantages of the present application clearer, the implementation mode of the present application will be further described in detail with reference to the accompanying drawings. The technical solution of the embodiment of the present application and the technical effect produced by the technical solution of the present application are explained below by describing several exemplary implementation modes. It should be pointed out that the following implementation modes can refer to, draw lessons from or combine with each other, and the same terms, similar features and similar implementation steps in different implementation modes are not described repeatedly.

[0046] Figure 1The flowchart of the adaptive load balancing processing method and system based on the blockchain network provided by the embodiment of the present application is shown. It should be understood that in other embodiments, the order of some steps of the adaptive load balancing processing method based on the blockchain network of this embodiment can be shared with each other according to actual needs, or some steps can be omitted or maintained. The detailed steps of the adaptive load balancing processing method based on the blockchain network include:

[0047] Step S110, obtaining the load state characteristic distribution of each blockchain node among multiple blockchain nodes in the blockchain network, wherein the load state characteristic distribution includes multiple continuous load state characteristics of each blockchain node, and the load state characteristic includes resource usage indicators of multiple resource usage tags.

[0048] In this embodiment, the blockchain service system starts to perform load monitoring tasks by connecting to the blockchain network and collecting load state feature distributions from each blockchain node in the blockchain network. These load state feature distributions are obtained through a series of continuous measurements, and each measurement records the resource usage of the node at a specific point in time.

[0049] For example, the blockchain service system may collect data on resource usage labels such as CPU usage, memory usage, and network bandwidth usage of node A in the past hour. These data form a time series that shows the load status characteristic distribution of node A during this period.

[0050] Step S120, pairing each resource usage indicator covered by the load state characteristic to generate a pairing set of each resource usage indicator of the load state characteristic, wherein the resource usage indicator pairing set is a sequence of two resource usage indicators, the resource usage indicator pairing set includes a key resource usage indicator and a derived resource usage indicator, and the load balancing condition degree of the key resource usage indicator is greater than the load balancing condition degree of the derived resource usage indicator.

[0051] In this embodiment, the blockchain service system then analyzes the collected load status characteristics. For example, it pays special attention to resource usage indicators that have an important impact on node load balancing. The blockchain service system can pair these resource usage indicators to form a resource usage indicator pairing set.

[0052] Taking node A as an example, suppose the blockchain service system finds that CPU usage and memory occupancy are two key resource usage indicators, and their load balancing condition is relatively high. The blockchain service system pairs these two indicators to form a resource usage indicator pairing set. In this resource usage indicator pairing set, CPU usage is marked as a key resource usage indicator because it has a more direct and significant impact on node performance; while memory usage is regarded as a derived resource usage indicator. Although it is also important, its impact is relatively minor.

[0053] Step S130, obtaining a load balancing control graph of the multiple blockchain nodes. If the key resource usage indicator is a unique resource usage tag, the recorded resource usage indicators of the load balancing control graph do not cover the key resource usage indicator, the recorded resource usage indicators include the derived resource usage indicators, and the first resource usage indicator cluster associated with the derived resource usage indicators in the load balancing control graph includes resource usage indicators with unique resource usage tags, then an updated load balancing scheme is generated based on the resource usage indicator pairing set to the load balancing control graph, wherein the load balancing condition degree of the resource usage indicator with the unique resource usage tag is not less than the load balancing condition degree of the key resource usage indicator.

[0054] In this embodiment, the blockchain service system then obtains the load balancing control diagram of the current blockchain network, which shows the resource allocation and load status of each node in the current blockchain network. The blockchain service system can check the recorded resource usage indicators in the load balancing control diagram to determine whether the load balancing solution needs to be updated.

[0055] Assume that in the load balancing control graph, the recorded resource usage indicators of node A only include memory usage, but not CPU usage, a key resource usage indicator. At the same time, the blockchain service system notices that the first resource usage indicator cluster associated with memory usage in the load balancing control graph contains indicators with other unique resource usage labels, such as disk I / O rate, and the load balancing condition of these indicators is not lower than CPU usage. In this case, the blockchain service system can generate a new load balancing scheme based on the resource usage indicator pairing set. The load balancing scheme takes into account the correlation between CPU usage and memory usage, as well as their joint impact on node load balancing. The blockchain service system can apply this new load balancing scheme to the load balancing control graph to optimize the resource allocation and load status of node A.

[0056] Specifically, the new load balancing solution may include adjusting the task allocation strategy of node A to reduce the number of CPU-intensive tasks, thereby reducing CPU utilization; at the same time, reducing memory occupancy by optimizing the memory management strategy. These adjustments are aimed at achieving load balancing of node A and improving its overall performance.

[0057] Based on the above steps, by accurately acquiring and analyzing the load status characteristic distribution of each node in the blockchain network, an effective pairing of key resource usage indicators and derived resource usage indicators is achieved. Not only the real-time and continuity of resource usage indicators are taken into account, but also the load balancing capability of the blockchain network is significantly improved by identifying unique resource usage tags and performing targeted load balancing regulation.

[0058] Specifically, by real-time monitoring and analyzing the load status characteristic distribution of blockchain nodes, it is possible to timely discover and handle load imbalances, effectively avoiding the problem of network performance degradation caused by uneven resource allocation. The resource usage indicators are paired, especially the key resource usage indicators and the derivative resource usage indicators are distinguished, so that the formulation of the load balancing strategy is more accurate and targeted. This resource pairing method can more accurately reflect the actual usage of node resources, thereby improving the effect of load balancing. In addition, the role of unique resource usage labels in load balancing is particularly considered. By incorporating these special resources into the load balancing control diagram and generating and updating the load balancing scheme in a targeted manner, it is ensured that these key resources can be reasonably allocated and used. This not only improves the utilization rate of resources, but also enhances the stability and reliability of the network. In addition, the embodiment of the present application can dynamically adjust the load balancing strategy according to the real-time load status of the blockchain network, realizing efficient management and optimization of the network load. This adaptive control capability enables the present invention to adapt to blockchain networks of different scales and structures, and has wide applicability and scalability. Therefore, by accurately acquiring and analyzing the load status characteristic distribution of blockchain nodes, effective pairing of key resource usage indicators and derivative resource usage indicators is achieved, and load balancing regulation of unique resource usage tags is supported, which significantly improves the load balancing capability and network performance of the blockchain network.

[0059] In one possible implementation, if the key resource usage indicator is a unique resource usage tag, the recorded resource usage indicator includes the key resource usage indicator, the recorded resource usage indicator includes the derived resource usage indicator, and the first resource usage indicator cluster includes resource usage indicators with unique resource usage tags, then the resource usage indicator pairing set is integrated into the second resource usage indicator cluster associated with the key resource usage indicator in the load balancing control diagram.

[0060] In this embodiment, when the blockchain service system is processing the load balancing problem of the blockchain network, if a key resource usage indicator is found, such as "GPU usage rate of a specific model", this is a unique resource usage label, which means that not all nodes have this resource or the measurement method of using this resource. At the same time, the blockchain service system also notices that this key resource usage indicator and related derivative resource usage indicators, such as "GPU memory occupancy rate", have been recorded in the load balancing control diagram.

[0061] In this case, the blockchain service system further checks the load balancing control graph, especially the resource usage indicator clusters associated with these resource usage indicators. For example, if the first resource usage indicator cluster (the cluster directly associated with the derived resource usage indicator "GPU memory occupancy") contains not only common resource usage indicators, but also indicators with other unique resource usage labels, such as "GPU temperature", these indicators with unique resource usage labels are also crucial to the stable operation of the node, and their load balancing condition is also quite high.

[0062] Since the key resource usage indicator "GPU usage rate of a specific model" has been recorded in the load balancing control diagram, and its related derivative resource usage indicators are also included, the blockchain service system decided not to create a new load balancing solution, but to integrate the resource usage indicator pairing set obtained from the current analysis (i.e., the pairing of "GPU usage rate of a specific model" and "GPU memory occupancy") into the existing load balancing control diagram.

[0063] Specifically, the blockchain service system can add this resource usage indicator pairing set to the second resource usage indicator cluster associated with the key resource usage indicator "GPU usage rate of a specific model". The second resource usage indicator cluster can be a load balancing control diagram specifically established for indicators with unique resource usage tags, which is used to more finely control the allocation and load balancing of these special resources.

[0064] Through this integration, the blockchain service system can ensure that when adjusting the load balancing strategy, the impact of key resource usage indicators and derived resource usage indicators, as well as their interaction with indicators of other unique resource usage tags, are taken into account, which helps to improve the overall performance and stability of the blockchain network.

[0065] In one possible implementation, if the key resource usage indicator is a unique resource usage tag, the recorded resource usage indicator includes the key resource usage indicator, the recorded resource usage indicator includes the derived resource usage indicator, and the first resource usage indicator cluster does not cover the resource usage indicator with the unique resource usage tag, then the resource usage indicator pairing set and the first resource usage indicator cluster are integrated into the second resource usage indicator cluster associated with the key resource usage indicator in the load balancing control diagram.

[0066] In this embodiment, the blockchain service system identifies a key resource usage indicator while continuously monitoring and analyzing the load balancing of the blockchain network. The key resource usage indicator is a unique resource usage label, such as "I / O rate of a specific storage device". This key resource usage indicator is crucial for certain blockchain nodes with specific configurations because it directly affects the data processing capabilities and response speeds of these nodes.

[0067] The blockchain service system further checks the load balancing control diagram and finds that this key resource usage indicator and its related derivative resource usage indicators (such as "storage device occupied space") have been recorded in the diagram. However, the first resource usage indicator cluster directly associated with the derivative resource usage indicator does not contain indicators with other unique resource usage tags, which means that although the blockchain service system is already monitoring these key and derivative resource usage indicators, the current load balancing strategy may not have fully utilized or taken into account the particularity and importance of these unique resource tags. In order to optimize the load balancing effect, the blockchain service system needs to take further actions. According to this situation, the blockchain service system can integrate the resource usage indicator pairing set (i.e., the pairing of "specific storage device I / O rate" and "storage device occupied space") and all indicators in the first resource usage indicator cluster into the second resource usage indicator cluster associated with the key resource usage indicator in the load balancing control diagram.

[0068] The second resource usage indicator cluster can be specially set up for unique resource usage tags to more accurately manage and optimize the load distribution of these special resources. Through this integration, the blockchain service system can ensure that when adjusting the load balancing solution, it can more comprehensively consider the impact of these unique resource tags, thereby formulating a more accurate and effective load balancing strategy. The completion of this step will help improve the performance of specific configuration nodes in the blockchain network, ensure that resources are more reasonably allocated and utilized, and thus improve the stability and efficiency of the entire network.

[0069] In one possible implementation, if the key resource usage indicator is not a unique resource usage label, the recorded resource usage indicator includes the key resource usage indicator, and the recorded resource usage indicator includes the derived resource usage indicator, then the resource usage indicator pairing set and the second resource usage indicator cluster associated with the key resource usage indicator in the load balancing control diagram are integrated into the first resource usage indicator cluster.

[0070] In this embodiment, when the blockchain service system processes a resource allocation task of a blockchain network, it will first pay attention to various resource usage indicators in order to perform effective load balancing. In this process, the blockchain service system pays special attention to a key resource usage indicator, such as "CPU usage rate", which is not a unique resource usage label, but an indicator that all blockchain nodes generally pay attention to and monitor.

[0071] The blockchain service system begins to check the existing load balancing control diagram and confirms that the key resource usage indicator "CPU usage" has been recorded in the diagram, and the related derivative resource usage indicators, such as "CPU temperature", are also recorded. These indicators are essential for evaluating the health and performance of the node. Next, the blockchain service system can view the second resource usage indicator cluster associated with the key resource usage indicator "CPU usage" in the load balancing control diagram. This cluster may contain other indicators related to CPU performance, such as "CPU cache hit rate" or "CPU core frequency", which together provide the blockchain service system with a comprehensive perspective on the node CPU usage.

[0072] Since the key resource usage indicator "CPU usage rate" is not a unique resource usage label and has been recorded in the load balancing control diagram, and its related derivative resource usage indicators are also included, the blockchain service system will then perform the integration operation.

[0073] Specifically, the blockchain service system can integrate the resource usage indicator pairing set obtained from the current analysis (i.e., the pairing of "CPU usage rate" and "CPU temperature") and all indicators in the second resource usage indicator cluster associated with "CPU usage rate" in the load balancing control diagram into the first resource usage indicator cluster.

[0074] The first resource usage indicator cluster can be a more core and comprehensive cluster in the load balancing control diagram, which is used to reflect the overall resource usage of blockchain network nodes. Through this integration method, the blockchain service system can ensure that when considering the load balancing strategy, it not only pays attention to the key resource usage indicators, but also comprehensively considers the related derivative resource usage indicators and other related indicators, so as to formulate a more comprehensive and accurate load balancing plan.

[0075] In this way, the load status of each blockchain node in the blockchain network can be evaluated more accurately, thereby optimizing resource allocation and improving the overall performance and stability of the network.

[0076] In one possible implementation, if the key resource usage indicator is a unique resource usage tag, the recorded resource usage indicators do not cover the key resource usage indicator, the recorded resource usage indicators include the derived resource usage indicators, and the first resource usage indicator cluster does not cover the resource usage indicators of the unique resource usage tag, then the resource usage indicator pairing set is integrated into the first resource usage indicator cluster.

[0077] In this embodiment, the blockchain service system is performing resource monitoring and load balancing configuration on a new blockchain network node. In this process, the blockchain service system identifies a key resource usage indicator, which is a unique resource usage tag, such as "the write speed of a specific model of SSD". This indicator is crucial for evaluating the performance of the blockchain node because it directly affects the write efficiency of blockchain data and the node response speed. However, when checking the recorded resource usage indicators, the blockchain service system found that the "write speed of a specific model of SSD" of this unique resource usage tag was not included. However, related derivative resource usage indicators, such as "SSD remaining life", have been recorded. At the same time, the first resource usage indicator cluster does not cover indicators of other unique resource usage tags.

[0078] In this case, in order to more comprehensively evaluate the performance of the node and optimize the load balancing strategy, the blockchain service system decided to integrate the resource usage indicator pairing set (i.e., the pairing of "write speed of a specific model of SSD" and "remaining life of SSD") into the first resource usage indicator cluster. This ensures that when adjusting the load balancing, the blockchain service system can fully consider the impact of this unique resource usage label on node performance, thereby making more reasonable resource allocation decisions.

[0079] Alternatively, if the key resource usage indicator is not a unique resource usage tag, the recorded resource usage indicators do not cover the key resource usage indicator, and the recorded resource usage indicators include the derived resource usage indicator, the resource usage indicator pairing set is integrated into the first resource usage indicator cluster.

[0080] In this embodiment, in another scenario, the blockchain service system is monitoring a blockchain network that has been running for a period of time. This time, the key resource usage indicator that the blockchain service system is concerned about is "network bandwidth utilization", which is not a unique resource usage label, but a performance indicator common to all nodes. When analyzing the recorded resource usage indicators, the blockchain service system found that "network bandwidth utilization" was not recorded, but its related derivative resource usage indicator "data transmission delay" had been monitored and recorded. Since "network bandwidth utilization" is crucial to evaluating network transmission efficiency and communication capabilities between nodes, the blockchain service system believes it is necessary to include it in the monitoring scope.

[0081] Since the key resource usage indicator "network bandwidth utilization" is not a unique resource usage label and is not included in the recorded resource usage indicators, but the related derivative resource usage indicators have been recorded, the blockchain service system can integrate the resource usage indicator pairing set (i.e., the pairing of "network bandwidth utilization" and "data transmission delay") into the first resource usage indicator cluster. Doing so can help the blockchain service system more accurately evaluate the communication performance of the network and adjust the load balancing strategy when necessary to optimize network transmission efficiency.

[0082] In one possible implementation, if the recorded resource usage indicators include the key resource usage indicators and the recorded resource usage indicators do not cover the derived resource usage indicators, the resource usage indicator pairing set is integrated into the second resource usage indicator cluster associated with the key resource usage indicator in the load balancing control diagram.

[0083] In this embodiment, when the blockchain service system performs resource management and load balancing configuration on a blockchain network, it can first comprehensively monitor and record the resource usage of each blockchain node in the blockchain network. In this process, the blockchain service system pays special attention to some key resource usage indicators, such as "memory usage rate", which is an important indicator for evaluating node performance and processing power. During the monitoring process, the blockchain service system found that the key resource usage indicator "memory usage rate" has been recorded in the recorded resource usage indicators. However, when the blockchain service system tried to analyze the related derivative resource usage indicators, such as "memory leakage rate" or "memory fragmentation rate", it was found that these derivative indicators were not included in the recorded resource usage indicators.

[0084] Since the derived resource usage indicators are also very important for comprehensively evaluating the memory usage and performance of nodes, the blockchain service system decided to take corresponding measures to improve the monitoring system. In this case, the blockchain service system can choose to integrate the resource usage indicator pairing set (i.e., the pairing of "memory usage rate" and related derived resource usage indicators) into the second resource usage indicator cluster associated with the key resource usage indicator "memory usage rate" in the load balancing control diagram.

[0085] Specifically, the blockchain service system can find the second resource usage indicator cluster associated with "memory usage rate" in the load balancing control diagram, and this cluster may already contain some other indicators related to memory usage. Then, the blockchain service system can add derivative resource usage indicators such as "memory leakage rate" and "memory fragmentation rate" to this cluster, and pair and associate them with "memory usage rate".

[0086] Through this integration, the blockchain service system can more comprehensively monitor and analyze the memory usage of nodes, including key resource usage indicators and derived resource usage indicators. This will help the blockchain service system to more accurately evaluate the performance and health of nodes, and adjust the load balancing strategy when necessary to ensure stable operation and efficient processing of the network.

[0087] In a possible implementation, step S120 may include:

[0088] Step S121: From the resource usage indicators covered by the load status characteristics, a resource usage indicator with the greatest load balancing condition is obtained as a key resource usage indicator.

[0089] In this embodiment, when monitoring the load status of a blockchain node, the blockchain service system first collects various resource usage indicators of the blockchain node over a period of time, such as CPU usage, memory occupancy, network bandwidth utilization, etc. Then, the blockchain service system can analyze the degree of influence of these indicators in load balancing, that is, the load balancing condition. For example, if the fluctuation of CPU usage has the greatest impact on the overall performance of the network node, then CPU usage will be selected as the key resource usage indicator.

[0090] Step S122: From the resource usage indicators covered by the load status characteristics, a resource usage indicator whose load balancing condition is lower than the key resource usage indicator is obtained as a derived resource usage indicator.

[0091] After determining that CPU usage is the key resource usage indicator, the blockchain service system can further analyze the correlation and impact between other resource usage indicators and CPU usage. For example, memory usage may have a certain correlation with CPU usage. When CPU usage increases, memory usage may also increase. However, the impact of memory usage on load balancing is not as great as that of CPU usage. Therefore, memory usage will be selected as a derivative resource usage indicator.

[0092] Step S123, obtaining a recording time domain from the load state characteristics.

[0093] When analyzing the load status characteristics, the blockchain service system will pay attention to the changes in these resource usage indicators over a period of time. This period of time is the recording time domain, which can be data from the past few minutes, hours, or days. By recording the time domain, the blockchain service system can more comprehensively understand the changing trends and periodic characteristics of resource usage indicators.

[0094] Step S124, aggregating the key resource usage indicator, the derived resource usage indicator and the recording time domain to generate the resource usage indicator pairing set.

[0095] Finally, the blockchain service system can aggregate selected key resource usage indicators (such as CPU usage), derived resource usage indicators (such as memory occupancy), and recording time domains (such as data from the past hour). In this way, a resource usage indicator pairing set is formed, which contains the key information needed to evaluate the load status of network nodes. This pairing set will be used for subsequent load balancing strategy formulation and resource optimization adjustment.

[0096] In a possible implementation, the resource usage indicator pairing set further includes a recording time domain, and step S130 may include:

[0097] Step S131 , aggregating the key resource usage indicator and the recording time domain to generate a combined sequence of the key resource usage indicator.

[0098] Step S132: Aggregate the derived resource usage indicator with the recording time domain to generate a combined sequence of the derived resource usage indicator.

[0099] Step S133: generating the updated load balancing solution according to the key resource usage indicator and the derived resource usage indicator.

[0100] Step S134: In the load balancing control graph, the combination sequence of the key resource usage indicators and the combination sequence of the derived resource usage indicators are loaded into the associated resource usage indicator cluster of the updated load balancing solution.

[0101] In this embodiment, in a blockchain network, the blockchain service system is responsible for monitoring and optimizing the load balancing of multiple blockchain nodes. The blockchain service system first collects the load status characteristic distribution of each blockchain node by connecting to the blockchain network. These load status characteristic distributions include multiple continuous resource usage indicators of the node in the past period of time, such as CPU usage, memory occupancy, disk I / O, etc.

[0102] After analyzing the collected data, the blockchain service system identified "CPU usage" as the resource usage indicator with the highest load balancing condition, i.e., the key resource usage indicator. At the same time, the blockchain service system noticed that "memory occupancy" had a strong correlation with CPU usage, but its load balancing condition was relatively low, so it was considered as a derived resource usage indicator.

[0103] In further processing, the blockchain service system determines the record time domain related to these resource usage indicators, such as the data of the past hour. The blockchain service system aggregates the key resource usage indicator "CPU usage rate" with the record time domain of this hour, and generates a combined sequence containing the changes in CPU usage rate within this hour. Similarly, the blockchain service system also aggregates the derived resource usage indicator "memory occupancy rate" with the record time domain of this hour, and generates a combined sequence of memory occupancy rate.

[0104] Next, the blockchain service system starts to generate and update the load balancing plan based on the combined sequence of these two resource usage indicators. In this plan, the blockchain service system takes into account the correlation between CPU usage and memory occupancy, and predicts possible future load change trends based on historical data. The blockchain service system calculates the optimal resource allocation ratio for each blockchain node under the current load state, and formulates a corresponding task scheduling strategy to ensure that the load between nodes can be balanced.

[0105] Finally, the blockchain service system applies the generated updated load balancing scheme to the load balancing control graph. In the control graph, the blockchain service system finds the resource usage indicator cluster associated with the key resource usage indicator "CPU usage rate". The blockchain service system loads the combined sequence of CPU usage rate and the combined sequence of memory occupancy rate into this cluster, and adjusts the resource allocation rules within the cluster according to the new load balancing scheme. In this way, when a task request arrives in the blockchain network, the blockchain service system can allocate the task to the most appropriate node for execution according to the configuration information in the control graph, thereby achieving efficient load balancing.

[0106] In a possible implementation, step S133 includes:

[0107] Step S1331, perform quantitative evaluation on the key resource usage indicator and the derived resource usage indicator, analyze the weight, usage frequency, and correlation with other resource usage indicators of each of the key resource usage indicator and the derived resource usage indicator in the load state characteristics, and obtain an evaluation result.

[0108] Step S1332: Based on the evaluation results, predict the future resource requirements of each blockchain node, and based on the prediction results, calculate the amount of resources to be allocated to each blockchain node.

[0109] Step S1333: Generate a task migration plan according to the future resource demand and the amount of resources to be allocated, and use the task migration plan as solution data in the updated load balancing solution.

[0110] In this embodiment, in a complex blockchain network environment, the blockchain service system is responsible for monitoring and optimizing the load balancing of multiple blockchain nodes. The blockchain service system first continuously collects the load status characteristic distribution of each blockchain node through network connection. These data record in detail the resource usage of each node over a period of time.

[0111] Assume that in a certain monitoring cycle, the blockchain service system collects the resource usage data of node A in the past hour. After analysis, the blockchain service system identifies that the "CPU usage rate" fluctuates greatly in this hour and has a significant impact on node performance, so it is marked as a key resource usage indicator. At the same time, the "memory occupancy rate" which is closely related to the CPU usage rate is also identified as a derived resource usage indicator.

[0112] In the process of generating and updating the load balancing plan, the blockchain service system first aggregates the key resource usage indicator "CPU usage" with the recording time domain (i.e. the past hour). This process actually integrates the time series data of CPU usage to form a complete combined sequence containing timestamps and corresponding CPU usage values. This combined sequence clearly shows the changing trend and fluctuation of CPU usage in the past hour.

[0113] Similarly, the blockchain service system also aggregates the derived resource usage indicator "memory occupancy rate" with the same recording time domain to generate a combined sequence of memory occupancy rates, which also contains a timestamp and the corresponding memory occupancy rate value, reflecting the changes in memory occupancy rate over time.

[0114] With these two combined sequences, the blockchain service system can generate and update the load balancing plan based on them. The blockchain service system can deeply analyze the correlation between the two indicators, such as whether the memory usage rate increases when the CPU usage rate increases. At the same time, the blockchain service system will also refer to historical data and prediction models to predict the possible change trends of these resource usage indicators in the future.

[0115] Based on these analyses, the blockchain service system develops a new load balancing solution, which may include adjusting the task allocation strategy on node A to reduce the number of CPU-intensive tasks, thereby reducing CPU utilization; at the same time, reducing memory occupancy by optimizing the memory management strategy. These adjustments are aimed at achieving load balancing of node A and improving its overall performance.

[0116] Finally, the blockchain service system applies the generated updated load balancing scheme to the load balancing control graph. In the control graph, the blockchain service system finds the resource usage indicator cluster associated with the key resource usage indicator "CPU usage", which may already contain some other indicators related to CPU performance. The blockchain service system loads the combined sequence of CPU usage and the combined sequence of memory occupancy into this cluster, and adjusts the resource allocation rules within the cluster according to the new load balancing scheme. In this way, when a new task request arrives, the blockchain service system can allocate the task to the most appropriate node for execution according to the configuration information in the control graph, thereby achieving efficient load balancing of the entire blockchain network.

[0117] Figure 2 A blockchain service system 100 provided in an embodiment of the present application is shown, including a processor 1001, a memory 1003 and a program code stored on the memory 1003, and the processor 1001 executes the above program code to implement the steps of an adaptive load balancing processing method based on a blockchain network.

[0118] Figure 2 The blockchain service system 100 shown includes: a processor 1001 and a memory 1003. The processor 1001 and the memory 1003 are connected, such as through a bus 1002. Optionally, the blockchain service system 100 may also include a transceiver 1004, which may be used for data interaction between the blockchain service system and other blockchain service systems, such as data transmission and / or data reception. It should be noted that the transceiver 1004 is not limited to one in actual scheduling, and the structure of the blockchain service system 100 does not constitute a limitation on the embodiments of the present application.

[0119] Processor 1001 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array) or other programmable logic devices, transistor logic devices, hardware data structures or any combination thereof. It may implement or execute various exemplary logic blocks, modules and circuits described in conjunction with the transaction records disclosed in this application. Processor 1001 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0120] The bus 1002 may include a path to transmit information between the above components. The bus 1002 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus 1002 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 2 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0121] The memory 1003 may be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compressed optical disk, laser disk, optical disk, digital versatile disk, Blu-ray disk, etc.), magnetic disk storage medium, other magnetic storage devices, or any other medium that can be used to have or store program code and can be read by a computer, without limitation herein.

[0122] The memory 1003 is used to store program codes for executing the embodiments of the present application, and the execution is controlled by the processor 1001. The processor 1001 is used to execute the program codes stored in the memory 1003 to implement the steps shown in the above method embodiments.

[0123] An embodiment of the present application provides a computer-readable storage medium having program code stored thereon. When the program code is executed by a processor, the steps of the aforementioned method embodiment and the corresponding transaction records can be implemented.

[0124] It should be understood that, although each operation step is indicated by arrows in the flowchart of the embodiment of the present application, the implementation order of these steps is not limited to the order indicated by the arrows. Unless there is clear explanation in this article, in some implementation scenarios of the embodiment of the present application, the implementation steps in each flowchart can be performed in other orders based on demand. In addition, some or all of the steps in each flowchart may include multiple sub-steps or multiple stages according to the actual implementation scenario, and some or all of these sub-steps or stages may be executed at the same time, and each sub-step or stage in these sub-steps or stages may also be executed at different times respectively. In different scenarios at the execution time, the execution order of these sub-steps or stages can be flexibly configured based on demand, and the embodiment of the present application does not limit this.

[0125] The above is only an optional implementation method for some implementation scenarios of the present application. It should be pointed out that for ordinary technicians in this technical field, without departing from the technical concept of the scheme of the present application, other similar implementation methods based on the technical ideas of the present application are also within the protection scope of the embodiments of the present application.

Claims

1. An adaptive load balancing processing method based on blockchain network, characterized in that: The method comprises: Obtaining a load state feature distribution of each blockchain node among a plurality of blockchain nodes in a blockchain network, wherein the load state feature distribution includes a plurality of continuous load state features of each blockchain node, and the load state feature includes resource usage indicators of a plurality of resource usage tags; Pairing each resource usage indicator covered by the load state feature to generate a pairing set of each resource usage indicator of the load state feature, wherein the resource usage indicator pairing set is a sequence of two resource usage indicators, the resource usage indicator pairing set includes a key resource usage indicator and a derived resource usage indicator, and the load balancing condition degree of the key resource usage indicator is greater than the load balancing condition degree of the derived resource usage indicator; Obtain a load balancing control graph of the multiple blockchain nodes. If the key resource usage indicator is a unique resource usage tag, the recorded resource usage indicators of the load balancing control graph do not cover the key resource usage indicator, the recorded resource usage indicators include the derived resource usage indicators, and the first resource usage indicator cluster associated with the derived resource usage indicator in the load balancing control graph includes the resource usage indicator of the unique resource usage tag, then generate an update load balancing scheme to the load balancing control graph based on the resource usage indicator pairing set, wherein the load balancing condition degree of the resource usage indicator of the unique resource usage tag is not less than the load balancing condition degree of the key resource usage indicator; The pairing of resource usage indicators covered by the load state feature to generate a pairing set of resource usage indicators of the load state feature includes: From the resource usage indicators covered by the load state characteristics, obtaining the resource usage indicator with the greatest load balancing condition as the key resource usage indicator; From the resource usage indicators covered by the load state characteristics, obtaining a resource usage indicator whose load balancing condition is lower than the key resource usage indicator as a derived resource usage indicator; Acquire a recording time domain from the load state characteristic; Aggregating the key resource usage indicator, the derived resource usage indicator, and the recording time domain to generate the resource usage indicator pairing set; The resource usage indicator pairing set also includes a recording time domain, and the step of generating an update load balancing solution to the load balancing control graph based on the resource usage indicator pairing set includes: Aggregating the key resource usage indicator with the recording time domain to generate a combined sequence of the key resource usage indicator; Aggregating the derived resource usage indicator with the recording time domain to generate a combined sequence of the derived resource usage indicator; generating the updated load balancing solution according to the key resource usage indicator and the derived resource usage indicator; In the load balancing control graph, loading the combination sequence of the key resource usage indicators and the combination sequence of the derived resource usage indicators into the associated resource usage indicator cluster of the updated load balancing solution; The step of generating the updated load balancing solution according to the key resource usage indicator and the derived resource usage indicator comprises: Quantitatively evaluate the key resource usage indicator and the derived resource usage indicator, analyze the weight, usage frequency, and correlation between the key resource usage indicator and the derived resource usage indicator in the load state characteristics, and other resource usage indicators to obtain an evaluation result; Based on the evaluation results, predict the future resource requirements of each blockchain node, and based on the prediction results, calculate the amount of resources to be allocated to each blockchain node; A task migration plan is generated according to the future resource demand and the amount of resources to be allocated, and the task migration plan is used as solution data in the updated load balancing solution.

2. The method for adaptive load balancing based on blockchain network according to claim 1 is characterized in that: The method further comprises: If the key resource usage indicator is a unique resource usage label, the recorded resource usage indicator includes the key resource usage indicator, the recorded resource usage indicator includes the derived resource usage indicator, and the first resource usage indicator cluster includes resource usage indicators with unique resource usage labels, then the resource usage indicator pairing set is integrated into the second resource usage indicator cluster associated with the key resource usage indicator in the load balancing control diagram.

3. The adaptive load balancing processing method based on blockchain network according to claim 1 is characterized in that: The method further comprises: If the key resource usage indicator is a unique resource usage tag, the recorded resource usage indicator includes the key resource usage indicator, the recorded resource usage indicator includes the derived resource usage indicator, and the first resource usage indicator cluster does not cover the resource usage indicator of the unique resource usage tag, then the resource usage indicator pairing set and the first resource usage indicator cluster are integrated into the second resource usage indicator cluster associated with the key resource usage indicator in the load balancing control diagram.

4. The method for adaptive load balancing based on blockchain network according to claim 1 is characterized in that: The method further comprises: If the key resource usage indicator is not a unique resource usage label, the recorded resource usage indicator includes the key resource usage indicator, and the recorded resource usage indicator includes the derived resource usage indicator, then the resource usage indicator pairing set and the second resource usage indicator cluster associated with the key resource usage indicator in the load balancing control diagram are integrated into the first resource usage indicator cluster.

5. The method for adaptive load balancing based on blockchain network according to claim 1 is characterized in that: The method further comprises: If the key resource usage indicator is a unique resource usage tag, the recorded resource usage indicators do not cover the key resource usage indicator, the recorded resource usage indicators include the derived resource usage indicators, and the first resource usage indicator cluster does not cover resource usage indicators of the unique resource usage tag, integrating the resource usage indicator pairing set into the first resource usage indicator cluster; Alternatively, if the key resource usage indicator is not a unique resource usage tag, the recorded resource usage indicators do not cover the key resource usage indicator, and the recorded resource usage indicators include the derived resource usage indicator, the resource usage indicator pairing set is integrated into the first resource usage indicator cluster.

6. The method for adaptive load balancing based on blockchain network according to claim 1 is characterized in that: The method further comprises: If the recorded resource usage indicators include the key resource usage indicators and the recorded resource usage indicators do not cover the derived resource usage indicators, the resource usage indicator pairing set is integrated into a second resource usage indicator cluster associated with the key resource usage indicator in the load balancing control diagram.

7. A blockchain service system, characterized in that: It includes a processor and a computer-readable storage medium, wherein the computer-readable storage medium stores machine-executable instructions, and when the machine-executable instructions are executed by the processor, the adaptive load balancing processing method based on the blockchain network described in any one of claims 1 to 6 is implemented.

Images