Medical alliance chain dynamic security resource configuration method

Abstract

The invention discloses a medical alliance chain dynamic security resource configuration method, and relates to the technical field of communication, and the method comprises the following steps: counting a plurality of nodes in a medical alliance chain node network architecture, marking the nodes as link nodes, monitoring the operation state of each link node based on a preset dynamic monitoring period, and sending the monitored operation state to a server; and analyzing the comprehensive load evaluation index value of each link node, comparing the comprehensive load evaluation index value with a preset operation load index threshold value to generate an operation load evaluation label of each link node, and processing according to the operation load evaluation label of each link node to obtain the number of redundant backup nodes of each link node. According to the medical alliance chain system resource allocation method and system, accurate allocation of medical alliance chain system resources can be achieved, a resource allocation strategy and a redundant backup node starting mechanism can be adjusted according to the real-time load condition of each link node, and the operation efficiency and stability of the whole medical alliance chain system are improved.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and in particular to a method for dynamically configuring secure resources for a medical alliance chain. Background Art

[0002] With the continuous acceleration of the digitalization process of the medical industry and the explosive growth of medical data, in the medical alliance chain, each link node carries a large amount of medical data transmission, storage and processing tasks. Traditional medical information management methods often focus on data storage and simple access control, which can no longer meet the current needs for efficient and secure management of medical data, and are likely to affect the stable operation and service quality of the entire medical alliance chain.

[0003] The prior art, such as the invention patent with announcement number: CN113133024B, is a method and device for configuring network resources. By improving the limitations of the prior art on the tuning range and tuning effect of network resource configuration, the problem of optimizing the configuration of network resources for the entire local area network is realized. The method includes: obtaining detection data of multiple network devices, the detection data includes air interface data of the network devices; obtaining the path loss between multiple network devices based on the detection data of multiple network devices; obtaining network health scores corresponding to multiple network configurations through neural network algorithms and deep learning algorithms, and the multiple network configurations are determined based on the path loss between multiple network devices; selecting the network configuration with the highest network health score to configure multiple network devices.

[0004] The prior art, such as the invention patent with announcement number: CN113259999B, is a method and device for network resource configuration, the method comprising: a terminal device receives configuration information from a network device, the configuration information comprising information of a first threshold corresponding to at least one candidate cell, the first threshold comprising at least one of a Doppler frequency offset threshold, a timing advance TA change rate threshold or a Doppler frequency offset change rate threshold; the terminal device determines a target cell from at least one candidate cell according to the configuration information; the terminal device initiates a switch to the target cell.

[0005] It can be seen from the above scheme that the current resource allocation method usually only analyzes and processes the overall network resource configuration. When it comes to the medical alliance chain, due to the sensitivity of its data and the diversity of the functions of each link node, the accuracy and dynamic adaptability of resource allocation are extremely high. At this time, if the overall network resources are allocated only from a macro level, it is impossible to fully guarantee the efficient operation and data security of actual nodes in different business scenarios and dynamically changing environments. Therefore, the current general resource allocation method is difficult to meet the refined and dynamic needs of the complex network architecture of the medical alliance chain, and the overall intelligence and adaptability need to be further improved. Summary of the invention

[0006] In view of the deficiencies in the prior art, the present invention provides a method for dynamic security resource configuration of a medical alliance chain, which can effectively solve the problems involved in the above-mentioned background technology.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: The present invention provides a method for dynamic security resource configuration of a medical alliance chain. The method includes the following steps: S1, counting several nodes in the medical alliance chain node network architecture and marking them as link nodes; S2, based on a preset dynamic monitoring cycle, monitor the operating status of each link node within the dynamic monitoring cycle and analyze the comprehensive load evaluation index value of each link node; S3, based on the comprehensive load evaluation index value of each link node, and comparing it with a preset operation load index threshold, thereby generating an operation load evaluation label of each link node; S4, according to the operation load evaluation label of each link node, the number of redundant backup nodes of each link node is obtained through processing, and the resource configuration of each link node is performed.

[0008] As a preferred technical solution, the operating status of each link node is monitored, and the specific monitoring process is as follows: within a preset dynamic monitoring period, the operating status of each link node is monitored based on a preset dynamic monitoring frequency, and the operating status data of each link node is obtained, and the operating status data of each link node includes hardware performance parameters and data transmission parameters.

[0009] The hardware performance parameters include the CPU usage rate, memory occupancy rate, hard disk storage capacity consumption rate, hard disk average read and write speed and device temperature of each link node within the dynamic monitoring cycle.

[0010] The data transmission parameters include the cumulative number of bytes of data transmitted by each link node within the dynamic monitoring period, the average data transmission rate, the cumulative amount of transmitted data, the data packet loss rate and the network interface bandwidth utilization rate.

[0011] As a preferred technical solution, the comprehensive load evaluation index value of each link node is analyzed, and the specific analysis process is as follows: based on the hardware performance parameters, the hardware operation load index of each link node is obtained through analysis and processing.

[0012] Based on the data transmission parameters, the data transmission load index of each link node is obtained through analysis and processing.

[0013] According to the hardware operation load index of each link node and the data transmission load index of each link node, a comprehensive load evaluation index value of each link node is obtained through comprehensive analysis and processing.

[0014] The comprehensive load evaluation index value of each link node is a numerical result of quantifying the hardware operation load index of each link node and the data transmission load index of each link node, and is used to characterize the operation load degree of each link node.

[0015] As an optimal technical solution, the hardware operation load index of each link node is specifically analyzed as follows: extract the reference hardware performance parameters stored in the database, and the reference hardware performance parameters include reference CPU usage, reference memory occupancy, reference consumption speed of hard disk storage capacity, reference hard disk read and write speed, and device reference temperature.

[0016] According to the hardware performance parameters and the reference hardware performance parameters, the hardware operation load index of each link node is obtained through analysis and processing.

[0017] The hardware operation load index of each link node is a numerical result of quantifying the hardware performance parameters and the reference hardware performance parameters, and is used to characterize the hardware operation load status of each link node.

[0018] As an optimal technical solution, the data transmission load index of each link node is specifically analyzed as follows: extract the reference data transmission parameters stored in the database, and the reference data transmission parameters include the reference data transmission cumulative number of bytes, the reference data average transmission rate, the reference cumulative transmission data volume, the reference data packet loss rate and the reference network interface bandwidth utilization rate.

[0019] According to the data transmission parameters and the reference data transmission parameters, the data transmission load index of each link node is obtained by analysis and processing.

[0020] The data transmission load index of each link node is a numerical result of quantifying the data transmission parameter and the reference data transmission parameter, and is used to characterize the data transmission load degree of each link node.

[0021] As a preferred technical solution, the specific process of generating the operating load evaluation label of each link node is as follows: based on the comprehensive load evaluation index value of each link node and the preset operating load index threshold, the operating load evaluation label of each link node is generated by comparison.

[0022] The operation load evaluation label includes a normal operation load and an abnormal operation load.

[0023] If the operation load index of a link node is lower than or equal to a preset operation load index threshold, the operation load evaluation label of the link node is defined as the normal operation load.

[0024] If the operating load index of a link node is higher than a preset operating load index threshold, the operating load evaluation label of the link node is defined as an abnormal operating load.

[0025] As an optimal technical solution, the processing obtains the number of redundant backup nodes of each link node, and the specific process is as follows: based on the operating load evaluation label of each link node, if the operating load evaluation label of a link node is a normal operating load, the number of redundant backup nodes of the link node is defined as zero; if the operating load evaluation label of a link node is an abnormal operating load, the link node is marked as a link node that requires capacity expansion, thereby counting each link node that requires capacity expansion.

[0026] Based on the comprehensive load evaluation index value of each link node, the difference between the operating load index of each link node that needs to be expanded and the preset operating load index threshold is extracted and recorded as the expansion reference value. The expansion reference value of each link node that needs to be expanded is thus counted, and mapped and matched with the number of redundant backup nodes corresponding to each expansion reference value interval defined in the database to obtain the number of redundant backup nodes of each link node that needs to be expanded.

[0027] As a preferred technical solution, the comprehensive load evaluation index value of each link node is specifically formulated as follows: ,in, is the comprehensive load evaluation index value of the i-th link node, is the hardware operation load index of the i-th link node, is the data transmission load index of the i-th link node, is the hardware operation load index weight, is the data transmission load index weight, i is the number of each link node, , m is the number of link nodes.

[0028] As a preferred technical solution, the medical alliance chain dynamic security resource configuration method also includes dynamic security resource configuration of redundant backup nodes. The specific process is: based on the number of redundant backup nodes of each link node, each redundant backup node is counted.

[0029] During the preset configuration period, each redundant backup node is sensed and monitored to obtain the usage load data of each redundant backup node, including the usage access frequency, the maximum number of connections, and the average read and write operation rate of each redundant backup node.

[0030] Extract redundant backup node reference load data stored in the database, wherein the redundant backup node reference load data includes a reference usage access frequency, a reference maximum number of connected persons, and a reference average read and write operation rate.

[0031] Based on the usage load data of each redundant backup node and the redundant backup node reference load data, the usage load index of each redundant backup node is analyzed and processed. The usage load index of each redundant backup node is a numerical result of quantifying the usage load data of each redundant backup node and the redundant backup node reference load data, and is used to characterize the usage load degree of each redundant backup node.

[0032] The load index of each redundant backup node is compared with the load index threshold of the redundant backup node. If the load index of a redundant backup node is less than or equal to the load index threshold of the redundant backup node, storage resources are not configured for the redundant backup node. If the load index of a redundant backup node is greater than the load index threshold of the redundant backup node, storage resources are configured for the redundant backup node with the preset storage capacity.

[0033] As a preferred technical solution, each redundant backup node uses a load index, and the specific formula is as follows: ,in, Use the load index for the jth redundant backup node, Use the access frequency for the jth redundant backup node, For reference use access frequency, The maximum number of connections to the jth redundant backup node, For reference, the maximum number of connections. The average read and write operation rate of the jth redundant backup node, For reference average read and write operation rate, To use access frequency weights, is the maximum number of connections weight, is the average read and write operation rate weight, j is the number of each redundant backup node, , n is the number of redundant backup nodes, and e is a natural constant.

[0034] Compared with the prior art, the embodiments of the present invention have at least the following beneficial effects: (1) The present invention provides a medical alliance chain dynamic security resource configuration method to achieve accurate allocation of medical alliance chain system resources. It can adjust the resource allocation strategy and the activation mechanism of redundant backup nodes according to the real-time load of each link node, thereby improving the operating efficiency and stability of the entire medical alliance chain system. (2) By analyzing the comprehensive load evaluation index value of each link node, the present invention can effectively evaluate and grasp the operating efficiency and pressure status of each link node in the medical alliance chain system, providing a solid foundation for the optimization and stable operation of the system. At the same time, it provides a clear direction for the rational allocation of resources, which helps to achieve dynamic and accurate management of the medical alliance chain system; (3) The present invention generates an operation load evaluation tag for each link node and configures node backup resources based on the operation load evaluation tag, thereby improving the convenience and pertinence of management, facilitating long-term performance monitoring and trend analysis. By tracking and recording the changes in the evaluation tags of each link node in different time periods, potential performance problems and trend patterns can be discovered, thus ensuring the sustainable development and stable operation of the medical alliance chain system; (4) The present invention significantly enhances the reliability and stability of the system by analyzing the number of redundant backup nodes of each link node. By accurately calculating and configuring the number of redundant backup nodes, when the main link node fails or cannot work normally due to high load pressure, the redundant backup node can be quickly enabled to take over its work, ensuring that the transmission and processing of medical data are not interrupted, improving the scalability and adaptability of the system, and at the same time, helping to improve the security of the entire medical alliance chain. By reasonably distributing redundant backup nodes, the risk of data loss and leakage can be reduced, providing a strong guarantee for information security;

[0035] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 It is a schematic diagram of system module connection of the present invention; Figure 2 It is a scatter diagram of the relationship between the link node data transmission load index and the link node operation load index involved in the embodiment of the present invention. DETAILED DESCRIPTION

[0037] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0038] See also Figure 1 As shown, an embodiment of the present invention provides a method for dynamic security resource configuration of a medical alliance chain, including: S1, counting a number of nodes in the medical alliance chain node network architecture, and marking them as link nodes.

[0039] In this embodiment, the medical alliance chain node network architecture refers to a distributed network structure system composed of computer devices or systems corresponding to multiple related medical institution entities participating in the interaction, sharing and storage of medical data. In this architecture, each node has certain computing power, storage capacity and network communication capabilities. The nodes are interconnected through specific network protocols and communication links to form a mutually cooperative and relatively independent network entity.

[0040] For example, as one of the nodes, the hospital’s internal medical information system contains a large amount of patient medical records, medical records, medical images and other information. These hospital nodes transmit and interact with other nodes through high-speed network connections.

[0041] It should be noted that several nodes in the node network architecture are the key supporting elements for the effective operation of the entire medical alliance chain. These nodes cover multiple key roles and institutions in the medical field, including but not limited to nodes of hospitals at all levels and types, nodes of medical research institutions, and nodes of medical regulatory departments.

[0042] It should also be noted that several nodes in the statistical medical alliance chain node network architecture can use network detection technologies and tools, such as deploying special network scanning software, to send specific detection data packets in the network environment on which the medical alliance chain relies, and identify and locate active network devices and nodes based on the response mechanism of the network protocol.

[0043] S2, based on a preset dynamic monitoring cycle, monitors the operating status of each link node within the dynamic monitoring cycle and analyzes the comprehensive load evaluation index value of each link node.

[0044] In this embodiment, the operating status of each link node is monitored, and the specific monitoring process is as follows: within a preset dynamic monitoring period, the operating status of each link node is monitored based on a preset dynamic monitoring frequency, and the operating status data of each link node is obtained, and the operating status data of each link node includes hardware performance parameters and data transmission parameters.

[0045] It should be understood that the preset dynamic monitoring cycle needs to be flexibly customized according to the actual operating characteristics and business needs of the medical alliance chain, analyze the business traffic patterns of the medical alliance chain, and conduct a detailed analysis of the transmission of medical data in the alliance chain over the past period of time, including the peak and trough periods of data transmission. At the same time, considering the differences in the importance of each link node in the medical alliance chain, for core link nodes that undertake key medical services, such as central data exchange nodes in large hospitals or data analysis server nodes in medical research institutions, it is necessary to set a relatively shorter and more frequent monitoring cycle because any problems may have a significant impact on the operation of the entire alliance chain.

[0046] It is also necessary to understand that even if the monitoring cycle is preset, it may be adjusted according to specific circumstances in actual operation. In this embodiment, if the operating status data of each link node changes significantly and lasts for a long time, the system will reduce the monitoring cycle and monitor more frequently. If the operating status data of each link node is always in a stable state, the system will appropriately extend the monitoring cycle to save resources. Therefore, the preset monitoring cycle does not affect the essence of dynamic monitoring. It is just a way to manage and optimize the monitoring process. By reasonably presetting the monitoring cycle, the efficiency and resource utilization of the monitoring system can be maximized while ensuring timely detection of problems.

[0047] The hardware performance parameters include the CPU usage rate, memory occupancy rate, hard disk storage capacity consumption rate, hard disk average read and write speed and device temperature of each link node within the dynamic monitoring cycle.

[0048] It should be understood that the CPU usage is directly provided by the task manager of the operating system of each link node, and the memory occupancy rate can be obtained by professional system performance monitoring software, such as Prometheus, by reading the memory-related data structures and interfaces provided by the operating system to obtain memory usage information, thereby obtaining the memory occupancy rate.

[0049] It should also be understood that the hard disk storage capacity consumption rate can be calculated by centrally managing and monitoring the hard disk through a storage area network (SAN) controller, and the average hard disk read and write speed is calculated by CrystalDiskMark, a software tool for testing hard disk performance, which sends a large number of data read and write requests to the hard disk and measures the speed at which the hard disk completes these requests within a certain period of time.

[0050] It should be noted that the device temperature refers to the average temperature of the hardware devices of each link node.

[0051] The data transmission parameters include the cumulative number of bytes of data transmitted by each link node within the dynamic monitoring period, the average data transmission rate, the cumulative amount of transmitted data, the data packet loss rate and the network interface bandwidth utilization rate.

[0052] It should be understood that the cumulative number of bytes of data transmission can be calculated by capturing network data packets through the network protocol analysis tool Wireshark, and based on the size and number of data packets. The average data transmission rate can be calculated by sending test data to the server through the network speed test tool Speedtest and measuring the response time.

[0053] It should also be understood that the data packet loss rate can be calculated by performing a packet loss rate test using a network performance testing tool.

[0054] It should be noted that the network interface bandwidth utilization rate refers to the ratio of the actual amount of data transmitted by the network interface per unit time to the theoretical maximum amount of data transmitted, which reflects the utilization efficiency of the network interface. In this embodiment, the comprehensive load evaluation index value of each link node is analyzed, and the specific analysis process is as follows: based on the hardware performance parameters, the hardware operation load index of each link node is obtained by analysis and processing.

[0055] In this embodiment, the hardware operation load index of each link node is specifically analyzed as follows: extract reference hardware performance parameters stored in the database, and the reference hardware performance parameters include reference CPU usage, reference memory occupancy, reference consumption speed of hard disk storage capacity, reference hard disk read and write speed, and device reference temperature.

[0056] It should be noted that the database is used to store reference indicator data, and the reference indicator data includes first reference indicator data, second reference indicator data and third reference indicator data.

[0057] The first reference indicator data includes reference hardware performance parameters and reference data transmission parameters, as well as the number of redundant backup nodes corresponding to each expansion reference value interval and redundant backup node reference load data, and also includes an operating load index threshold and a redundant backup node usage load index threshold.

[0058] The second reference indicator data includes the CPU usage weight, memory occupancy weight, hard disk storage capacity consumption speed weight, hard disk average read and write speed weight and device temperature weight, and also includes the cumulative number of bytes of data transmitted weight, average data transmission rate weight, cumulative data transmission volume weight, data packet loss rate weight and network interface bandwidth utilization weight.

[0059] The third reference indicator data includes the hardware operation load index weight and the data transmission load index weight, and also includes the access frequency weight, the maximum number of connections weight and the average read and write operation rate weight.

[0060] According to the hardware performance parameters and the reference hardware performance parameters, the hardware operation load index of each link node is obtained through analysis and processing.

[0061] The hardware operation load index of each link node is a numerical result of quantifying the hardware performance parameters and the reference hardware performance parameters, and is used to characterize the hardware operation load status of each link node.

[0062] In a specific embodiment, the hardware operation load index of each link node is specifically expressed as follows: , in, is the hardware operation load index of the i-th link node, is the CPU usage of the i-th link node, For reference CPU usage, is the memory occupancy rate of the i-th link node, For reference memory usage, is the hard disk storage capacity consumption rate of the i-th link node, It is the reference consumption speed of hard disk storage capacity. is the average hard disk read and write speed of the i-th link node, For reference read and write speed of hard disk, is the device temperature of the i-th link node, is the device reference temperature, is the CPU usage weight, is the memory usage weight, The speed weight of the hard disk storage capacity consumption. is the average read and write speed weight of the hard disk, is the device temperature weight, i is the number of each link node, , m is the number of link nodes, and e is a natural constant.

[0063] It should be noted that the CPU usage weight has a value range between 0 and 1. In the present embodiment, the CPU usage weight is a CPU usage weight preset in the database, which represents a numerical value of the influence of the CPU usage on the hardware operation load index of the link node. When used, the preset CPU usage weight can be directly obtained from the database, and the corresponding relationship can be a pre-set mapping relationship. For example, the node CPU usage and the CPU usage weight preset in the database form a mapping set, and the real-time CPU usage is input into the mapping set to obtain the CPU usage weight, wherein the mapping relationship is one-to-one.

[0064] It should be noted that the memory occupancy weight has a value range between 0 and 1. In the present embodiment, the memory occupancy weight is a memory occupancy weight preset in the database, which represents a numerical value of the influence of the memory occupancy on the hardware operation load index of the link node. When used, the preset memory occupancy weight can be directly obtained from the database, and the corresponding relationship can be a pre-set mapping relationship. For example, the node memory occupancy and the memory occupancy weight preset in the database form a mapping set, and the real-time memory occupancy is input into the mapping set to obtain the memory occupancy weight, wherein the mapping relationship is one-to-one.

[0065] It should be noted that the hard disk storage capacity consumption speed weight value has a value range between 0 and 1. In this embodiment, the hard disk storage capacity consumption speed weight value is a hard disk storage capacity consumption speed weight value preset in the database, which represents the numerical value of the influence of the hard disk storage capacity consumption speed on the hardware operation load index of the link node. When used, the preset hard disk storage capacity consumption speed weight value can be directly obtained from the database, and the corresponding relationship can be a pre-set mapping relationship. For example, the node hard disk storage capacity consumption speed and the hard disk storage capacity consumption speed weight value preset in the database form a mapping set, and the real-time hard disk storage capacity consumption speed is input into the mapping set to obtain the hard disk storage capacity consumption speed weight value, wherein the mapping relationship is one-to-one correspondence.

[0066] It should be noted that the hard disk average read and write speed weight has a value range between 0 and 1. In this embodiment, the hard disk average read and write speed weight is the hard disk average read and write speed weight preset in the database, which represents the numerical value of the influence of the hard disk average read and write speed on the hardware operation load index of the link node. When used, the preset hard disk average read and write speed weight can be directly obtained from the database, and the corresponding relationship can be a pre-set mapping relationship. For example, the node hard disk average read and write speed and the hard disk average read and write speed weight preset in the database form a mapping set, and the real-time hard disk average read and write speed is input into the mapping set to obtain the hard disk average read and write speed weight, wherein the mapping relationship is one-to-one correspondence.

[0067] It should be noted that the device temperature weight has a value range between 0 and 1. In this embodiment, the device temperature weight is a device temperature weight preset in the database, which represents the numerical value of the influence of the device temperature on the hardware operation load index of the link node. When used, the preset device temperature weight can be directly obtained from the database, and the corresponding relationship can be a pre-set mapping relationship. For example, the node device temperature and the device temperature weight preset in the database form a mapping set, and the real-time device temperature is input into the mapping set to obtain the device temperature weight, wherein the mapping relationship is one-to-one.

[0068] It should also be noted that in this embodiment, the hardware operation load index of each link node is obtained according to the CPU usage rate, memory occupancy rate, hard disk storage capacity consumption rate, average hard disk read and write speed and device temperature, taking into account the mutual influence between these parameters. For example, when the CPU usage rate of a link node is high, it means that the central processing unit of the node is performing a large number of computing tasks and its processing capacity is facing great pressure. If the memory usage rate is also high at this time, then the superposition of these two may cause a serious decline in system performance, because the high memory usage rate may cause the CPU to encounter bottlenecks in the data exchange and storage process, thereby further increasing the hardware operation load. If the hard disk storage capacity consumption rate is low at this time, this may alleviate the pressure on the overall hardware to a certain extent, because the lower hard disk storage capacity consumption rate means that the system has relatively fewer read and write operations on the hard disk, and the hard disk can have more resources to respond to requests from other hardware components. When the average hard disk read and write speed is fast, even if the CPU usage rate and memory occupancy rate are high, the hard disk can quickly respond to data read and write requests and provide the required data to the CPU and memory, thereby And to a certain extent, it can reduce the overall pressure of hardware operation. On the contrary, if the average read and write speed of the hard disk is slow, then when the CPU utilization rate and memory occupancy rate are high, it may become the bottleneck of the entire hardware system. If the device temperature rises, it may cause the CPU to downclock or throttle to prevent overheating, thereby reducing the CPU utilization rate. Because the CPU processing power decreases, it cannot handle the same load. High temperature may also affect the stability and performance of the memory. At the same time, the increase in hard disk temperature may affect its read and write performance, resulting in a decrease in the average read and write speed of the hard disk. If the system attempts to perform a large number of I / O operations at high temperature, it may accelerate the consumption of hard disk storage capacity and cause the average read and write speed of the hard disk to decrease. The hardware operation load index obtained by comprehensively considering these parameters can more comprehensively reflect the actual operation status and pressure-bearing ability of the link node hardware. When the hardware operation load index of a link node is high, it may be the unfavorable result of the superposition of these factors. In-depth analysis and comprehensive optimization measures are needed to ensure that the hardware of the link node can operate stably and efficiently, improve the reliability and performance of the entire system, and avoid the risk of hardware failure.

[0069] In a specific embodiment, by analyzing the hardware operation load index of each link node, the hardware operation performance and pressure status of each key node in the medical alliance chain system can be effectively measured and controlled, providing strong support for the stable operation and optimization and upgrading of the system.

[0070] Based on the data transmission parameters, the data transmission load index of each link node is obtained through analysis and processing.

[0071] In this embodiment, the data transmission load index of each link node is specifically analyzed as follows: extract the reference data transmission parameters stored in the database, and the reference data transmission parameters include the reference data transmission cumulative number of bytes, the reference data average transmission rate, the reference cumulative transmission data volume, the reference data packet loss rate and the reference network interface bandwidth utilization rate.

[0072] According to the data transmission parameters and the reference data transmission parameters, the data transmission load index of each link node is obtained by analysis and processing.

[0073] The data transmission load index of each link node is a numerical result of quantifying the data transmission parameter and the reference data transmission parameter, and is used to characterize the data transmission load degree of each link node.

[0074] In a specific embodiment, the data transmission load index of each link node is specifically expressed as follows: , in, is the data transmission load index of the i-th link node, is the cumulative number of bytes of data transmission of the i-th link node, Cumulative number of bytes transferred for reference data, is the average data transmission rate of the i-th link node, is the average transmission rate of reference data, is the cumulative amount of data transmitted by the i-th link node, For reference, the cumulative amount of data transmitted is is the data packet loss rate of the i-th link node, is the reference data packet loss rate, is the network interface bandwidth usage of the i-th link node, To refer to the network interface bandwidth usage, is the weight of the accumulated bytes of data transmission, is the average data transmission rate weight, is the weight of the accumulated data transmission volume, is the packet loss rate weight, is the network interface bandwidth utilization weight, i is the number of each link node, , m is the number of link nodes, and e is a natural constant.

[0075] It should be noted that the weight of the cumulative number of bytes of data transmission has a value range between 0 and 1. In the present embodiment, the weight of the cumulative number of bytes of data transmission is a preset weight of the cumulative number of bytes of data transmission in the database, which represents the numerical value of the influence of the cumulative number of bytes of data transmission on the data transmission load index of the link node. When used, the preset weight of the cumulative number of bytes of data transmission can be directly obtained from the database, and the corresponding relationship can be a pre-set mapping relationship. For example, the cumulative number of bytes of data transmission of the node and the weight of the cumulative number of bytes of data transmission preset in the database form a mapping set, and the real-time cumulative number of bytes of data transmission is input into the mapping set to obtain the weight of the cumulative number of bytes of data transmission, wherein the mapping relationship is one-to-one.

[0076] It should be noted that the data average transmission rate weight has a value range between 0 and 1. In the present embodiment, the data average transmission rate weight is a preset data average transmission rate weight in a database, which represents a numerical value of the influence of the data average transmission rate on the data transmission load index of the link node. When used, the preset data average transmission rate weight can be directly obtained from the database, and the corresponding relationship can be a pre-set mapping relationship. For example, the node data average transmission rate and the preset data average transmission rate weight in the database form a mapping set, and the real-time data average transmission rate is input into the mapping set to obtain the data average transmission rate weight, wherein the mapping relationship is one-to-one.

[0077] It should be noted that the cumulative transmission data volume weight has a value range between 0 and 1. In the present embodiment, the cumulative transmission data volume weight is a cumulative transmission data volume weight preset in a database, which represents a numerical value of the influence of the cumulative transmission data volume on the data transmission load index of the link node. When used, the preset cumulative transmission data volume weight can be directly obtained from the database, and the corresponding relationship can be a pre-set mapping relationship. For example, the cumulative transmission data volume of the node and the cumulative transmission data volume weight preset in the database form a mapping set, and the real-time cumulative transmission data volume is input into the mapping set to obtain the cumulative transmission data volume weight, wherein the mapping relationship is one-to-one correspondence.

[0078] It should be noted that the data packet loss rate weight has a value range between 0 and 1. In the present embodiment, the data packet loss rate weight is a data packet loss rate weight preset in a database, which represents a numerical value of the influence of the data packet loss rate on the data transmission load index of the link node. When used, the preset data packet loss rate weight can be directly obtained from the database, and the corresponding relationship can be a pre-set mapping relationship. For example, the node data packet loss rate and the data packet loss rate weight preset in the database form a mapping set, and the real-time data packet loss rate is input into the mapping set to obtain the data packet loss rate weight, wherein the mapping relationship is one-to-one.

[0079] It should be noted that the network interface bandwidth usage weight has a value range between 0 and 1. In this embodiment, the network interface bandwidth usage weight is a network interface bandwidth usage weight preset in a database, which represents a numerical value of the degree of influence of the network interface bandwidth usage weight on the data transmission load index of the link node. When used, the preset network interface bandwidth usage weight can be directly obtained from the database, and the corresponding relationship can be a pre-set mapping relationship. For example, the node network interface bandwidth usage weight and the network interface bandwidth usage weight preset in the database form a mapping set, and the real-time network interface bandwidth usage weight is input into the mapping set to obtain the network interface bandwidth usage weight, wherein the mapping relationship is one-to-one correspondence.

[0080] It should also be noted that in this embodiment, the data transmission load index of each link node is obtained by processing according to the cumulative number of bytes of data transmission, the average data transmission rate, the cumulative amount of transmitted data, the data packet loss rate and the network interface bandwidth utilization rate, taking into account the mutual influence between these parameters. For example, when the cumulative number of bytes of data transmission of a link node is high, it means that the node has transmitted a large amount of data within a period of time, which shows that the node bears a large load in terms of the scale of the data transmission task. If the average data transmission rate is low at this time, then this indicates that the data transmission efficiency is relatively low, and a large amount of data is accumulated waiting for transmission, which will increase the pressure on the node in data transmission, making it possible for it to face difficulties in processing subsequent data transmission tasks, such as overflow of the data buffer area, backlog of the transmission queue, etc., which may lead to increased delays and instability in data transmission. When the average data transmission rate is high, even if the cumulative number of bytes of data transmission is large, it is possible to complete the data transmission task relatively quickly, thereby alleviating the data transmission to a certain extent. Pressure. If the cumulative amount of transmitted data is large, it means that the node has been performing frequent data transmission activities over a long period of time. This is not only a test of the node's current transmission capacity, but may also pose a challenge to its long-term stability and resource management capabilities. If the data packet loss rate is also high at this time, it means that more data has been lost during the data transmission process. Data packet loss will not only affect the integrity of data transmission, but may also trigger the start of the retransmission mechanism, further increasing the burden of data transmission and the load of the node. An increase in bandwidth utilization means that more data is transmitted through the network interface, so the cumulative number of bytes of data transmission will also increase accordingly. An increase in bandwidth utilization may also cause network congestion, which in turn affects the average rate of data transmission. If the network interface is close to its maximum bandwidth, new data packets may queue up for transmission, which may reduce the average data transmission rate. At the same time, when the network interface bandwidth utilization reaches or approaches the maximum value, new data packets may be discarded due to insufficient bandwidth resources, resulting in an increase in data packet loss rate. The data transmission load index obtained by comprehensively considering these parameters can more comprehensively reflect the actual working status and pressure-bearing ability of the link node in data transmission. When the data transmission load index of a link node is high, it may be the unfavorable result of the superposition of these factors. In-depth analysis and comprehensive optimization measures are needed to ensure that the link node can transmit data stably and efficiently, improve the reliability and performance of the entire network system, and avoid the risk of failure.

[0081] In a specific embodiment, by analyzing the data transmission load index of each link node, it is possible to accurately reflect the operating pressure faced by the link node in the data transmission link, provide accurate guidance for the rational allocation of resources, help achieve refined network management, and provide key data support and decision-making basis for the refined network management of the medical alliance chain, thereby promoting the digital construction of the medical industry to a higher level.

[0082] According to the hardware operation load index of each link node and the data transmission load index of each link node, a comprehensive load evaluation index value of each link node is obtained through comprehensive analysis and processing.

[0083] The comprehensive load evaluation index value of each link node is a numerical result of quantifying the hardware operation load index of each link node and the data transmission load index of each link node, and is used to characterize the operation load degree of each link node.

[0084] In a specific embodiment, the comprehensive load evaluation index value of each link node is specifically expressed as follows: ,in, is the comprehensive load evaluation index value of the i-th link node, is the hardware operation load index of the i-th link node, is the data transmission load index of the i-th link node, is the hardware operation load index weight, is the data transmission load index weight, i is the number of each link node, , m is the number of link nodes.

[0085] It should be noted that the hardware operation load index weight has a value range between 0 and 1. In this embodiment, the hardware operation load index weight is a hardware operation load index weight preset in the database, which represents the numerical value of the influence of the hardware operation load index on the operation load index of the link node. When used, the preset hardware operation load index weight can be directly obtained from the database, and the corresponding relationship can be a pre-set mapping relationship. For example, the node hardware operation load index and the hardware operation load index weight preset in the database form a mapping set, and the real-time hardware operation load index is input into the mapping set to obtain the hardware operation load index weight, wherein the mapping relationship is one-to-one correspondence.

[0086] It should be noted that the data transmission load index weight has a value range between 0 and 1. In the present embodiment, the data transmission load index weight is a data transmission load index weight preset in a database, which indicates the numerical value of the influence of the data transmission load index on the operation load index of the link node. When used, the preset data transmission load index weight can be directly obtained from the database, and the corresponding relationship can be a pre-set mapping relationship. For example, the node data transmission load index and the data transmission load index weight preset in the database form a mapping set, and the real-time data transmission load index is input into the mapping set to obtain the data transmission load index weight, wherein the mapping relationship is one-to-one.

[0087] It should also be noted that in this embodiment, the comprehensive load evaluation index value of each link node is obtained according to the hardware operation load index of each link node and the data transmission load index of each link node, taking into account the mutual influence between these parameters. For example, when the hardware operation load index of a link node is high, it means that the hardware device of the node is facing greater pressure when processing tasks, the CPU usage rate may be close to saturation, the memory occupancy rate is high, or the reading and writing of the storage device are frequently close to the limit, etc. If the data transmission load index is low at this time, that is, the data inflow and outflow of the node are relatively small, and the frequency and scale of data transmission are within an acceptable range, then this can alleviate the overall operating pressure to a certain extent, because the lower data transmission load will not further increase the burden on the hardware, and the hardware can have more spare capacity to cope with the current task. However, when the data transmission load index is high, it means that the link node needs to frequently receive, process and send a large amount of data. If the hardware operation load is high at this time If the index is also at a high level, the node may be in trouble. For example, a large amount of data requires fast CPU processing and memory caching, but because the hardware itself is already running at high load, the data processing speed may slow down, and data may be queued for processing, which in turn causes increased data transmission delays. Furthermore, if the hardware operation load index is low but the data transmission load index is high, although the hardware has certain potential to cope with data transmission tasks, if it is in this state for a long time, it may cause the hardware equipment to age faster due to continuous high data traffic impact, or single-point bottlenecks may appear on certain key hardware components. For example, the network interface may overheat or erroneously due to a large amount of data transmission, affecting the quality and stability of data transmission. The link node operation load index obtained by comprehensively considering these parameters can more comprehensively reflect the actual operating status and pressure-bearing ability of the node, so as to ensure that the link node can operate stably and efficiently, improve the reliability of the entire alliance chain, and avoid the risk of failure.

[0088] See also Figure 2As shown, a scatter diagram of the relationship between the link node data transmission load index and the link node operation load index involved in the embodiment of the present invention is shown, wherein the horizontal axis is the link node data transmission load index, and the vertical axis is the link node operation load index. The multiple scatter points in the figure are the link node operation load indexes corresponding to the link node data transmission load index involved in this embodiment. It can be clearly seen from the figure that with the increase of the data transmission load index, the link node operation load index generally shows an upward trend. This is because when the data transmission load index increases, the operating pressure of the link node increases. However, the distribution of the scatter points does not show a strict linear relationship, but has a certain discreteness, which reflects that in the actual operating environment, in addition to the data transmission load index, there are also There are many other factors that will affect the link node operation load index. When the data transmission load index of a link node increases, it may mean that the node needs to handle more data traffic and more frequent data interaction tasks, which will indeed increase its operating pressure and thus cause the operation load index to rise. However, due to the influence of factors such as the hardware operation load index, even if the data transmission load index increases, the change in the operation load index may be limited. For example, if the hardware operation load index is low, indicating that the hardware device of the node has sufficient processing power to cope with the increased data transmission tasks, then even if the data transmission load index increases, the operation load index may not increase significantly, and may even remain relatively stable or even decrease due to efficient hardware processing.

[0089] In a specific embodiment, by analyzing the comprehensive load evaluation index value of each link node, the operating efficiency and pressure status of each link node in the medical alliance chain system can be effectively evaluated and grasped, providing a solid foundation for the optimization and stable operation of the system. At the same time, it provides a clear direction for the rational allocation of resources, which helps to achieve dynamic and precise management of the medical alliance chain system.

[0090] S3, based on the comprehensive load evaluation index value of each link node, and comparing it with a preset operation load index threshold, thereby generating an operation load evaluation label for each link node.

[0091] In this embodiment, the specific process of generating the operation load evaluation label of each link node is as follows: based on the comprehensive load evaluation index value of each link node and the preset operation load index threshold, the operation load evaluation label of each link node is generated by comparison.

[0092] It should be understood that the operating load index threshold refers to the key reference value stored in the database for measuring whether the operating load status of the link node is within a reasonable range. The operating load index threshold is based on the long-term operation monitoring and performance analysis of the medical alliance chain system, combined with the actual needs of medical services and the carrying capacity of system resources. By comparing the comprehensive load evaluation index value of each link node with the operating load index threshold, it is possible to quickly determine whether the operating load of the link node is within the normal range.

[0093] The operation load evaluation label includes a normal operation load and an abnormal operation load.

[0094] If the operation load index of a link node is lower than or equal to a preset operation load index threshold, the operation load evaluation label of the link node is defined as the normal operation load.

[0095] If the operating load index of a link node is higher than a preset operating load index threshold, the operating load evaluation label of the link node is defined as an abnormal operating load.

[0096] In a specific embodiment, by generating an operation load evaluation tag for each link node and configuring node backup resources based on the operation load evaluation tag, the convenience and pertinence of management are improved, which is helpful for long-term performance monitoring and trend analysis. By tracking and recording the changes in the evaluation tags of each link node in different time periods, potential performance problems and trend patterns can be discovered to ensure the sustainable development and stable operation of the medical alliance chain system.

[0097] S4, according to the operation load evaluation label of each link node, the number of redundant backup nodes of each link node is obtained through processing, and the resource configuration of each link node is performed.

[0098] In this embodiment, the processing obtains the number of redundant backup nodes of each link node, and the specific process is as follows: based on the operating load evaluation label of each link node, if the operating load evaluation label of a link node is a normal operating load, the number of redundant backup nodes of the link node is defined as zero; if the operating load evaluation label of a link node is an abnormal operating load, the link node is marked as a link node that requires capacity expansion, thereby counting each link node that requires capacity expansion.

[0099] Based on the comprehensive load evaluation index value of each link node, the difference between the operating load index of each link node that needs to be expanded and the preset operating load index threshold is extracted and recorded as the expansion reference value. The expansion reference value of each link node that needs to be expanded is thus counted, and mapped and matched with the number of redundant backup nodes corresponding to each expansion reference value interval defined in the database to obtain the number of redundant backup nodes of each link node that needs to be expanded.

[0100] In a specific embodiment, by analyzing the number of redundant backup nodes of each link node, the reliability and stability of the system are significantly enhanced. By accurately calculating and configuring the number of redundant backup nodes, when the main link node fails or cannot work normally due to high load pressure, the redundant backup node can be quickly enabled to take over its work, ensuring that the transmission and processing of medical data are not interrupted, improving the scalability and adaptability of the system, and at the same time, helping to improve the security of the entire medical alliance chain. By reasonably distributing redundant backup nodes, the risk of data loss and leakage can be reduced, providing strong protection for information security.

[0101] It should be noted that the resource configuration of each link node can be completed through the server management console.

[0102] The server management console is the core device for configuring link node resources. It is usually built based on open source server management software. Through the server management console, the hardware resources of the server nodes can be directly configured and managed. In a specific embodiment, for the configuration of CPU resources, the CPU core number, main frequency, power management mode and other parameters can be adjusted in the console. For example, on a hospital node server in the medical alliance chain, if it is found that the CPU load is too high when processing the transcoding task of a large amount of medical imaging data, some CPU cores on other idle servers can be dynamically allocated to the node server through the console to improve its data processing capability.

[0103] For the configuration of memory resources, you can add or remove memory bars in the console and adjust the memory allocation strategy, such as setting the memory cache size and the use of virtual memory. For example, when a node in a medical research institution is performing large-scale data analysis and finds that insufficient memory leads to slow data processing, you can add more memory bars or optimize memory use through the server management console to allocate more memory to key data processing processes.

[0104] In this embodiment, the medical alliance chain dynamic security resource configuration method also includes dynamic security resource configuration of redundant backup nodes. The specific process is: based on the number of redundant backup nodes of each link node, each redundant backup node is counted.

[0105] During the preset configuration period, each redundant backup node is sensed and monitored to obtain the usage load data of each redundant backup node, including the usage access frequency, the maximum number of connections, and the average read and write operation rate of each redundant backup node.

[0106] It should be noted that the access frequency can be used to capture data packets using Wireshark, and a filter can be set to display only data packets related to the target redundant backup node, and then the access frequency can be calculated based on the number of captured data packets and the time span.

[0107] The maximum number of connected persons can be obtained by using network management software to check the number of users connected to the node, thereby obtaining the maximum number of connected persons.

[0108] The average read and write operation rate can be obtained by testing the read and write speed through the CrystalDiskMark tool and calculating the average value of the read and write operation rate within a preset period.

[0109] Extract redundant backup node reference load data stored in the database, wherein the redundant backup node reference load data includes a reference usage access frequency, a reference maximum number of connected persons, and a reference average read and write operation rate.

[0110] Based on the usage load data of each redundant backup node and the redundant backup node reference load data, the usage load index of each redundant backup node is analyzed and processed. The usage load index of each redundant backup node is a numerical result of quantifying the usage load data of each redundant backup node and the redundant backup node reference load data, and is used to characterize the usage load degree of each redundant backup node.

[0111] According to the load index of each redundant backup node, it is compared with the redundant backup node load index threshold stored in the database. If the load index of a redundant backup node is less than or equal to the redundant backup node load index threshold, storage resources are not configured for the redundant backup node. If the load index of a redundant backup node is greater than the redundant backup node load index threshold, storage resources are configured for the redundant backup node with the preset storage capacity.

[0112] It should be understood that the storage resource configuration of the redundant backup node can execute the preset storage capacity allocation through the storage management interface provided by the computer operating system, and map the allocated storage resources to the redundant backup node through a network storage protocol such as iSCSI. At the same time, the corresponding storage driver and configuration file are installed on the redundant backup node, such as the remote management tool SSH, to identify and use the newly allocated storage resources.

[0113] In a specific embodiment, each redundant backup node uses a load index, and the specific formula is as follows: ,in, Use the load index for the jth redundant backup node, Use the access frequency for the jth redundant backup node, For reference use access frequency, The maximum number of connections to the jth redundant backup node, For reference, the maximum number of connections. The average read and write operation rate of the jth redundant backup node, For reference average read and write operation rate, To use access frequency weights, is the maximum number of connections weight, is the average read and write operation rate weight, j is the number of each redundant backup node, , n is the number of redundant backup nodes, and e is a natural constant.

[0114] It should be noted that the access frequency weight has a value range between 0 and 1. In the present embodiment, the access frequency weight is a preset access frequency weight in the database, which indicates the numerical value of the influence of the access frequency on the redundant backup node usage load index. When used, the preset access frequency weight can be directly obtained from the database, and the corresponding relationship can be a pre-set mapping relationship. For example, the node access frequency and the access frequency weight preset in the database form a mapping set, and the real-time access frequency is input into the mapping set to obtain the access frequency weight, wherein the mapping relationship is one-to-one.

[0115] It should be noted that the maximum number of connections weight has a value range between 0 and 1. In the present embodiment, the maximum number of connections weight is a maximum number of connections weight preset in a database, which represents a numerical value of the influence of the maximum number of connections on the redundant backup node usage load index. When used, the preset maximum number of connections weight can be directly obtained from the database, and the corresponding relationship can be a pre-set mapping relationship. For example, the maximum number of connections of a node and the maximum number of connections weight preset in a database form a mapping set, and the real-time maximum number of connections is input into the mapping set to obtain the maximum number of connections weight, wherein the mapping relationship is one-to-one.

[0116] It should be noted that the average read and write operation rate weight has a value range between 0 and 1. In this embodiment, the average read and write operation rate weight is the average read and write operation rate weight preset in the database, which represents the numerical value of the influence of the average read and write operation rate on the redundant backup node usage load index. When used, the preset average read and write operation rate weight can be directly obtained from the database, and the corresponding relationship can be a pre-set mapping relationship. For example, the node average read and write operation rate and the average read and write operation rate weight preset in the database form a mapping set, and the real-time average read and write operation rate is input into the mapping set to obtain the average read and write operation rate weight, wherein the mapping relationship is one-to-one correspondence.

[0117] It should also be noted that in this embodiment, the use load index of each redundant backup node is obtained according to the use access frequency, the maximum number of connections and the average read and write operation rate of each redundant backup node, taking into account the mutual influence between these parameters. For example, when the use access frequency of a redundant backup node is high, it means that the node is requested for service more times per unit time, which shows that the node undertakes more frequent tasks in data interaction, and its load pressure is relatively large at the access level. If the maximum number of connections is low at this time, it means that the number of devices or users establishing connections with the node at the same time is small, which alleviates its overall load pressure to a certain extent, because a small number of connections means relatively less concurrent occupation of system resources, and relatively lower concurrent demand for data processing and transmission. When the average read and write operation rate is fast, the node can quickly process data read and write requests, and even if the access frequency and the maximum number of connections are high, it is possible to respond efficiently, thereby To a certain extent, it can alleviate the perception of load pressure. If the average read and write operation rate is low, then when faced with a high access frequency and a large number of connections, it may lead to data backlog and processing delays, greatly increasing the load pressure of the node. If a redundant backup node has a high access frequency and the maximum number of connections is close to its upper limit, and the average read and write operation rate cannot meet the requirements of fast response, then this node may face the risk of slow response, data transmission interruption, and even system crash. The redundant backup node usage load index obtained by comprehensively considering these parameters can more comprehensively reflect the actual working status and load bearing capacity of the node. When a redundant backup node has a high usage load index, it may be the unfavorable result of the superposition of these factors. In-depth analysis and comprehensive optimization measures are needed to allocate resources to ensure that the redundant backup nodes can operate stably and efficiently, improve the reliability and performance of the entire system, and avoid the risk of failure.

[0118] The following takes the four different groups of redundant backup nodes involved in this embodiment as an example. When the average read and write operation rates of the four groups of redundant backup nodes are all 80 kilobytes per second, the reference access frequency is defined as 50 times per minute, the reference maximum number of connections is defined as 100 people, the reference average read and write operation rate is defined as 100 kilobytes per second, the access frequency weight is defined as 0.35, the maximum number of connections weight is defined as 0.4, and the average read and write operation rate weight is defined as 0.25. Based on the different access frequencies and the maximum number of connections, the redundant backup node usage load index obtained through processing is as follows: Table 1 Redundant backup node usage load index: Group Use access frequency Maximum number of connections Redundant backup nodes use load index Group 1 20 70 1.87 Group 2 40 90 2.01 Group 3 60 110 2.16 Group 4 80 130 2.32 ; Combined with the above table, we can see that the usage load index of the fourth group of redundant backup nodes is the highest, which means that compared with other groups, the fourth group of redundant backup nodes faces the most prominent operating pressure. In specific examples, for redundant backup nodes with high access frequency and maximum number of connections, the complexity of their data processing and the pressure on system resource allocation are relatively large, which means that their related resources need to be optimized to ensure that they can operate stably and efficiently.

[0119] In a specific embodiment, by analyzing the load index of each redundant backup node, it can be clearly indicated which redundant backup nodes are under greater work pressure, providing an accurate basis for the rational allocation and dynamic adjustment of resources, helping to achieve refined system maintenance and management, and providing reliable protection for the stable operation and data security of the medical alliance chain system.

[0120] In a specific embodiment, by providing a dynamic security resource configuration method for a medical alliance chain, accurate allocation of medical alliance chain system resources is achieved. The resource allocation strategy and the activation mechanism of redundant backup nodes can be adjusted according to the real-time load conditions of each link node, thereby improving the operating efficiency and stability of the entire medical alliance chain system.

[0121] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0122] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that technicians in the relevant technical field can understand and use the present invention well. As long as they do not deviate from the structure of the present invention or exceed the scope defined by the present invention, they should all belong to the protection scope of the present invention.

Claims

1. A method for dynamic security resource configuration of a medical alliance chain, characterized by: The following steps are involved: S1, counts several nodes in the medical alliance chain node network architecture, marked as link nodes; S2, based on a preset dynamic monitoring cycle, monitor the operating status of each link node within the dynamic monitoring cycle and analyze the comprehensive load evaluation index value of each link node; S3, based on the comprehensive load evaluation index value of each link node, and comparing it with a preset operation load index threshold, thereby generating an operation load evaluation label of each link node; S4, according to the operation load evaluation label of each link node, the number of redundant backup nodes of each link node is obtained through processing, and the resource configuration of each link node is performed.

2. According to claim 1, a method for dynamic security resource configuration of a medical alliance chain is characterized by: The operation status of each link node is monitored, and the specific monitoring process is as follows: Within a preset dynamic monitoring period, the operating status of each link node is monitored based on a preset dynamic monitoring frequency, and the operating status data of each link node is obtained, wherein the operating status data of each link node includes hardware performance parameters and data transmission parameters; The hardware performance parameters include the CPU usage rate, memory occupancy rate, hard disk storage capacity consumption rate, hard disk average read and write speed and device temperature of each link node within the dynamic monitoring cycle; The data transmission parameters include the cumulative number of bytes of data transmitted by each link node within the dynamic monitoring period, the average data transmission rate, the cumulative amount of transmitted data, the data packet loss rate and the network interface bandwidth utilization rate.

3. According to claim 2, a method for dynamic security resource configuration of a medical alliance chain is characterized by: The comprehensive load evaluation index value of each link node is analyzed, and the specific analysis process is as follows: Based on the hardware performance parameters, the hardware operation load index of each link node is obtained through analysis and processing; Based on the data transmission parameters, the data transmission load index of each link node is obtained by analysis and processing; According to the hardware operation load index of each link node and the data transmission load index of each link node, a comprehensive load evaluation index value of each link node is obtained by comprehensive analysis and processing; The comprehensive load evaluation index value of each link node is a numerical result of quantifying the hardware operation load index of each link node and the data transmission load index of each link node, and is used to characterize the operation load degree of each link node.

4. According to claim 3, a method for dynamic security resource configuration of a medical alliance chain is characterized by: The hardware operation load index of each link node is analyzed in detail as follows: Extracting reference hardware performance parameters stored in a database, the reference hardware performance parameters including reference CPU usage, reference memory occupancy, reference consumption speed of hard disk storage capacity, reference hard disk read and write speed, and reference device temperature; According to the hardware performance parameters and the reference hardware performance parameters, the hardware operation load index of each link node is obtained by analysis and processing; The hardware operation load index of each link node is a numerical result of quantifying the hardware performance parameters and the reference hardware performance parameters, and is used to characterize the hardware operation load status of each link node.

5. According to claim 3, a method for dynamic security resource configuration of a medical alliance chain is characterized by: The data transmission load index of each link node is specifically analyzed as follows: Extracting reference data transmission parameters stored in a database, the reference data transmission parameters including reference data transmission cumulative number of bytes, reference data average transmission rate, reference cumulative transmission data volume, reference data packet loss rate and reference network interface bandwidth usage rate; According to the data transmission parameter and the reference data transmission parameter, the data transmission load index of each link node is obtained by analyzing and processing; The data transmission load index of each link node is a numerical result of quantifying the data transmission parameter and the reference data transmission parameter, and is used to characterize the data transmission load degree of each link node.

6. According to claim 1, a method for dynamic security resource configuration of a medical alliance chain is characterized by: The specific process of generating the operation load evaluation label of each link node is as follows: According to the comprehensive load evaluation index value of each link node and the preset operation load index threshold, the operation load evaluation label of each link node is generated by comparison; The operation load evaluation label includes normal operation load and abnormal operation load; If the operation load index of a link node is lower than or equal to a preset operation load index threshold, the operation load evaluation label of the link node is defined as a normal operation load; If the operating load index of a link node is higher than a preset operating load index threshold, the operating load evaluation label of the link node is defined as an abnormal operating load.

7. According to claim 6, a method for dynamic security resource configuration of a medical alliance chain is characterized by: The processing obtains the number of redundant backup nodes of each link node, and the specific process is as follows: Based on the operation load evaluation label of each link node, if the operation load evaluation label of a link node is a normal operation load, the number of redundant backup nodes of the link node is defined as zero; if the operation load evaluation label of a link node is an abnormal operation load, the link node is marked as a link node requiring capacity expansion, thereby counting the link nodes requiring capacity expansion; Based on the comprehensive load evaluation index value of each link node, the difference between the operating load index of each link node that needs to be expanded and the preset operating load index threshold is extracted and recorded as the expansion reference value. The expansion reference value of each link node that needs to be expanded is thus counted, and mapped and matched with the number of redundant backup nodes corresponding to each expansion reference value interval defined in the database to obtain the number of redundant backup nodes of each link node that needs to be expanded.

8. According to claim 3, a method for dynamic security resource configuration of a medical alliance chain is characterized by: The comprehensive load evaluation index value of each link node is as follows: ， in, is the comprehensive load evaluation index value of the i-th link node, is the hardware operation load index of the i-th link node, is the data transmission load index of the i-th link node, is the hardware operation load index weight, is the data transmission load index weight, i is the number of each link node, , m is the number of link nodes.

9. According to claim 1, a method for dynamic security resource configuration of a medical alliance chain is characterized by: It also includes dynamic security resource configuration for redundant backup nodes. The specific process is as follows: Based on the number of redundant backup nodes of each link node, count each redundant backup node; During the preset configuration period, each redundant backup node is sensed and monitored to obtain the usage load data of each redundant backup node, including the usage access frequency, the maximum number of connections, and the average read and write operation rate of each redundant backup node; Extracting redundant backup node reference load data stored in a database, wherein the redundant backup node reference load data includes a reference usage access frequency, a reference maximum number of connections, and a reference average read and write operation rate; Based on the usage load data of each redundant backup node and the redundant backup node reference load data, the usage load index of each redundant backup node is obtained by analyzing and processing, wherein the usage load index of each redundant backup node is a numerical result of quantifying the usage load data of each redundant backup node and the redundant backup node reference load data, and is used to characterize the usage load degree of each redundant backup node; The load index of each redundant backup node is compared with the load index threshold of the redundant backup node. If the load index of a redundant backup node is less than or equal to the load index threshold of the redundant backup node, storage resources are not configured for the redundant backup node. If the load index of a redundant backup node is greater than the load index threshold of the redundant backup node, storage resources are configured for the redundant backup node with the preset storage capacity.

10. A method for dynamic security resource configuration of a medical alliance chain according to claim 9, characterized in that: Each redundant backup node uses a load index, and the specific formula is as follows: ， in, Use the load index for the jth redundant backup node, Use the access frequency for the jth redundant backup node, For reference use access frequency, The maximum number of connections to the jth redundant backup node, For reference, the maximum number of connections. The average read and write operation rate of the jth redundant backup node, For reference average read and write operation rate, To use the access frequency weight, is the maximum number of connections weight, is the average read and write operation rate weight, j is the number of each redundant backup node, , n is the number of redundant backup nodes, and e is a natural constant.

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