CN119271500B

CN119271500B - Dynamic safety resource allocation method for medical alliance chain

Info

Publication number: CN119271500B
Application number: CN202411399173.5A
Authority: CN
Inventors: 杨策; 梁伟; 谢思齐; 陈林书; 王进
Original assignee: Hunan University of Science and Technology
Current assignee: Hunan University of Science and Technology
Priority date: 2024-10-09
Filing date: 2024-10-09
Publication date: 2025-07-11
Anticipated expiration: 2044-10-09
Also published as: CN119271500A

Abstract

The present invention discloses a method for dynamic security resource configuration of a medical alliance chain, which relates to the field of communication technology. The method comprises the following steps: counting a number of nodes in a medical alliance chain node network architecture, marking them as link nodes, monitoring the operating status of each link node based on a preset dynamic monitoring cycle, analyzing the comprehensive load evaluation index value of each link node, and comparing it with a preset operating load index threshold, thereby generating an operating load evaluation label of each link node, and obtaining the number of redundant backup nodes of each link node through processing according to the operating load evaluation label of each link node, and performing resource configuration of each link node. The present invention can realize accurate allocation of medical alliance chain system resources, and can adjust the resource allocation strategy and the activation mechanism of redundant backup nodes 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.

Description

Dynamic safety resource allocation method for medical alliance chain

Technical Field

The invention relates to the technical field of communication, in particular to a dynamic safety resource allocation method for a medical alliance chain.

Background

Along with the continuous acceleration of the digitization process of the medical industry and the explosive growth of medical data, in a medical alliance chain, each link node carries a large number of medical data transmission, storage and processing tasks, the traditional medical information management mode is often focused on the storage and simple access control of data, the current high-efficiency and safe management requirements on the medical data cannot be met, and the stable operation and the service quality of the whole medical alliance chain are easily influenced.

The prior art, such as the patent with the publication number of CN113133024B, is a method and a device for configuring network resources, and the problem of optimizing the configuration of the network resources of the whole local area network is realized by improving the limitation of the prior art on the optimizing range and the optimizing effect of the configuration of the network resources. The method comprises the steps of obtaining detection data of a plurality of network devices, wherein the detection data comprise air interface data of the network devices, obtaining path loss among the plurality of network devices according to the detection data of the plurality of network devices, obtaining network health scores corresponding to a plurality of network configurations through a neural network algorithm and a deep learning algorithm, determining the plurality of network configurations according to the path loss among the plurality of network devices, and selecting the network configuration with the highest network health score to configure the plurality of network devices.

The prior art, such as the patent with the publication number CN113259999B, is a method and a device for configuring network resources, the method comprises the steps that a terminal device receives configuration information from the network device, the configuration information comprises information of a first threshold value corresponding to at least one candidate cell, the first threshold value comprises at least one of a Doppler frequency shift threshold value, a timing advance TA change rate threshold value or a Doppler frequency shift change rate threshold value, the terminal device determines a target cell from the at least one candidate cell according to the configuration information, and the terminal device initiates switching to the target cell.

As can be seen from the above scheme, the current resource allocation method generally only analyzes and processes the overall network resource allocation, when the medical alliance chain is involved, the accuracy and dynamic adaptability to the resource allocation are extremely high due to the sensitivity of data and the diversity of functions of each link node, and at this time, if the overall network resource allocation is only performed from the macroscopic level, the efficient operation and data security of the actual node under different service scenes and dynamic changing environments cannot be fully ensured, so that the current general resource allocation method is difficult to meet the requirements of refinement and dynamics under the complex network architecture of the medical alliance chain, and the overall intellectualization and adaptability are still to be further improved.

Disclosure of Invention

Aiming at the defects of the prior art, the invention provides a dynamic safety resource allocation method for a medical alliance chain, which can effectively solve the problems related to the background art.

In order to achieve the above purpose, the invention is realized by the following technical proposal that the invention provides a dynamic safety resource allocation method of medical alliance chains,

S1, counting a plurality of nodes in a medical alliance link point network architecture, and marking the nodes as all link nodes;

s2, monitoring the running state of each link node in a dynamic monitoring period based on a preset dynamic monitoring period, and analyzing the comprehensive load evaluation index value of each link node;

s3, based on 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, and generating operation load evaluation labels of each link node;

S4, according to the operation load evaluation labels of the link nodes, the number of the redundant backup nodes of the link nodes is obtained through processing, and resource allocation of the link nodes is carried out.

The method comprises the following steps of monitoring the operation state of each link node based on a preset dynamic monitoring frequency in a preset dynamic monitoring period to obtain operation state data of each link node, wherein the operation state data of each link node comprises hardware performance parameters and data transmission parameters.

The hardware performance parameters comprise CPU utilization rate, memory occupancy rate, hard disk storage capacity consumption speed, hard disk average read-write speed and equipment temperature of each link node in a dynamic monitoring period.

The data transmission parameters comprise the data transmission accumulated byte number, the data average transmission rate, the accumulated transmission data quantity, the data packet loss rate and the network interface bandwidth utilization rate of each link node in the dynamic monitoring period.

The method comprises the following steps of analyzing and processing the comprehensive load evaluation index value of each link node based on the hardware performance parameters to obtain the hardware operation load index of each link node.

And based on the data transmission parameters, analyzing and processing to obtain the data transmission load index of each link node.

And comprehensively analyzing and processing according to the hardware operation load index of each link node and the data transmission load index of each link node to obtain the comprehensive load evaluation index value of each link node.

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 for representing the operation load degree of each link node.

The method comprises the following steps of extracting reference hardware performance parameters stored in a database, wherein the reference hardware performance parameters comprise reference CPU (Central processing Unit) utilization rate, reference memory occupancy rate, hard disk storage capacity reference consumption speed, hard disk reference read-write speed and equipment reference temperature.

And according to the hardware performance parameters and the reference hardware performance parameters, analyzing and processing to obtain the hardware operation load index of each link node.

The hardware operation load index of each link node is a numerical result of quantifying the hardware performance parameter and the reference hardware performance parameter, and is used for representing the hardware operation load state of each link node.

The data transmission load index of each link node is preferably calculated by extracting reference data transmission parameters stored in a database, wherein the reference data transmission parameters comprise reference data transmission accumulated byte number, reference data average transmission rate, reference accumulated transmission data quantity, reference data packet loss rate and reference network interface bandwidth utilization rate.

And according to the data transmission parameters and the reference data transmission parameters, analyzing and processing to obtain the data transmission load index of each link node.

The data transmission load index of each link node is a numerical result of quantizing the data transmission parameter and the reference data transmission parameter, and is used for representing the data transmission load degree of each link node.

The method comprises the following specific processes of generating the operation load evaluation labels of all the link nodes by comparing according to the comprehensive load evaluation index values of all the link nodes and the preset operation load index threshold value.

The operation load evaluation tag includes a normal operation load and an abnormal operation load.

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

If the operation load index of a certain link node is higher than a preset operation load index threshold, defining the operation load evaluation label of the link node as abnormal operation load.

Based on the operation load evaluation label of each link node, if the operation load evaluation label of a certain link node is normal operation load, the number of the redundant backup nodes of the link node is defined as zero, and if the operation load evaluation label of a certain link node is abnormal operation load, the link node is marked as a demand expansion link node, thereby counting each demand expansion link node.

And extracting the difference value between the operation load index of each demand expansion link node and a preset operation load index threshold value based on the comprehensive load evaluation index value of each link node, and recording the difference value as an expansion reference value, thereby counting the expansion reference value of each demand expansion link node, and carrying out mapping matching on the number of redundant backup nodes corresponding to each expansion reference value interval defined in a database to obtain the number of redundant backup nodes of each demand expansion link node.

As a preferable technical solution, the specific formula of the comprehensive load evaluation index value of each link node is as follows:

, wherein, An index value is evaluated for the integrated load of the i-th link node,The load index is run for the hardware of the i-th link node,The data transmission load index for the ith link node,For the hardware to run the load index weight,The load index weight for data transmission, i is the number of each link node,M is the number of link nodes.

As an optimized technical scheme, the medical alliance chain dynamic safety resource allocation method further comprises the step of carrying out dynamic safety resource allocation on the redundant backup nodes, and the specific process is that based on the number of the redundant backup nodes of each link node, each redundant backup node is counted.

And sensing and monitoring each redundant backup node in a preset configuration period to obtain the service load data of each redundant backup node, wherein the service load data specifically comprises the service access frequency, the maximum number of connected people and the average read-write operation rate of each redundant backup node.

And extracting redundant backup node reference load data stored in the database, wherein the redundant backup node reference load data comprises reference use access frequency, reference maximum number of connection persons and reference average read-write operation rate.

And analyzing and processing based on the use load data of each redundant backup node and the reference load data of the redundant backup node to obtain the use load index of each redundant backup node, wherein the use load index of each redundant backup node is a numerical result for quantifying the use load data of each redundant backup node and the reference load data of the redundant backup node and is used for representing the use load degree of each redundant backup node.

And comparing the usage load index of each redundant backup node with a usage load index threshold of the redundant backup node, if the usage load index of a certain redundant backup node is smaller than or equal to the usage load index threshold of the redundant backup node, not performing storage resource configuration on the redundant backup node, and if the usage load index of the certain redundant backup node is larger than the usage load index threshold of the redundant backup node, performing storage resource configuration on the redundant backup node with preset storage capacity.

As a preferred technical solution, the redundant backup nodes use a load index, and the specific formula is as follows:

, wherein, The load index is used for the jth redundant backup node,The access frequency is used for the jth redundant backup node,For reference purposes the access frequency is used,The maximum number of connections for the jth redundant backup node,For reference to the maximum number of people connected,The jth redundant backup node averages the read and write operation rates,To refer to the average read-write operation rate,In order to use the access frequency weight value,For the weight value of the maximum number of connected people,For the average read-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.

Compared with the prior art, the embodiment of the invention has at least the following beneficial effects:

(1) The invention realizes the accurate allocation of the resources of the medical alliance chain system by providing the dynamic safety resource allocation method of the medical alliance chain, can adjust the resource allocation strategy and the starting mechanism of the redundant backup node according to the real-time load condition of each link node, and improves the operation efficiency and the stability of the whole medical alliance chain system;

(2) According to the invention, through analyzing the comprehensive load evaluation index value of each link node, the operation efficiency and the pressure condition of each link node in the medical alliance link system can be effectively evaluated and mastered, a solid foundation is provided for the optimization and stable operation of the system, meanwhile, a clear direction is provided for the reasonable allocation of resources, and the dynamic and accurate management of the medical alliance link system is facilitated;

(3) According to the invention, the operation load evaluation labels of all the link nodes are generated, and the node backup resources are configured based on the operation load evaluation labels, so that the convenience and pertinence of management are improved, the long-term performance monitoring and trend analysis are facilitated, the potential performance problems and trend rules can be found by tracking and recording the evaluation label changes of all the link nodes in different time periods, and the sustainable development and stable operation of the medical alliance chain system are ensured;

(4) The invention remarkably enhances the reliability and stability of the system by analyzing the number of the redundant backup nodes of each link node, can rapidly start the redundant backup nodes to replace the operation of the main link node when the main link node fails or fails to work normally under high load pressure by accurately calculating and configuring the number of the redundant backup nodes, ensures the transmission and processing of medical data to be uninterrupted, improves the expandability and adaptability of the system, simultaneously is beneficial to improving the safety of the whole medical alliance link, can reduce the risk of data loss and leakage by reasonably distributing the redundant backup nodes, and provides a powerful guarantee for information safety;

Of course, it is not necessary for any one product to practice the invention to achieve all of the advantages set forth above at the same time.

Drawings

FIG. 1 is a schematic diagram of a system module connection of the present invention;

Fig. 2 is a scatter diagram of a relationship between a link node data transmission load index and a link node operation load index according to an embodiment of the present invention.

Detailed Description

The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

Referring to fig. 1, an embodiment of the present invention provides a method for configuring dynamic security resources of a medical alliance chain, including S1, counting a plurality of nodes in a medical alliance chain link point network architecture, and marking each link node.

In this embodiment, the medical alliance link point network architecture refers to a distributed network architecture formed by a plurality of computer devices or systems corresponding to related medical institution entities participating in medical data interaction, sharing and storage, in this architecture, each node has a certain computing capability, storage capability and network communication capability, and the nodes are connected with each other through a specific network protocol and a communication link to form a relatively independent network entity.

For example, a hospital is one of nodes, and a medical information system inside the hospital contains a large amount of information such as patient medical record data, diagnosis records, medical images and the like, and the hospital nodes are in data transmission and interaction with other nodes through high-speed network connection.

It should be noted that, the nodes in the node network architecture are key supporting elements that can effectively operate the whole medical alliance chain, and these nodes cover multiple key roles and organizations in the medical field, including but not limited to various hospital nodes at all levels, medical research institution nodes, medical supervision department nodes, and the like.

It should also be noted that, the nodes in the link point network architecture of the statistical medical alliance can use network detection technology and tools, such as deploying special network scanning software, to send specific detection data packets in the network environment supported by the medical alliance chain, and identify and locate active network devices and nodes according to the response mechanism of the network protocol.

S2, based on a preset dynamic monitoring period, monitoring the running state of each link node in the dynamic monitoring period, and analyzing the comprehensive load evaluation index value of each link node.

In this embodiment, the monitoring of the operation state of each link node specifically includes monitoring the operation state of each link node based on a preset dynamic monitoring frequency in a preset dynamic monitoring period, and obtaining operation state data of each link node, where the operation state data of each link node includes a hardware performance parameter and a data transmission parameter.

It should be understood that the preset dynamic monitoring period needs to be flexibly customized according to the actual operation characteristics and service requirements of the medical alliance chain, the service flow rule of the medical alliance chain is analyzed, the transmission condition of medical data in the alliance chain in a period of time is analyzed in detail, the transmission condition comprises a peak period and a valley period of data transmission, and meanwhile, the importance difference of all link nodes in the medical alliance chain is considered, and for a core link node bearing key medical services, such as a central data exchange node of a large hospital or a data analysis server node of a medical scientific research institution, a relatively short and more frequent monitoring period needs to be set because once a problem occurs, the operation of the whole alliance chain may be greatly influenced.

It should be further understood that even if the monitoring period is preset, in actual operation, the monitoring period may be adjusted according to specific situations, in this embodiment, if the operation status data of each link node has a relatively obvious change and a relatively long duration, the system may reduce the monitoring period, perform more frequent monitoring, and if the operation status data of each link node is always in a stable state, the system may properly prolong the monitoring period, so as to save resources. Therefore, the preset monitoring period does not affect the essence of dynamic monitoring, but is only a mode for managing and optimizing the monitoring process, and the efficiency and the resource utilization rate of the monitoring system can be improved to the greatest extent while the timely problem discovery is ensured through reasonable preset of the monitoring period.

It should be understood that the CPU utilization is directly provided by a task manager of the operating system of each link node, and the memory occupancy may be obtained by acquiring memory usage information by reading a memory related data structure and an interface provided by the operating system through professional system performance monitoring software, such as promethaus, so as to obtain the memory occupancy.

It should be further understood that the storage capacity consumption speed of the hard disk may be calculated by centrally managing and monitoring the hard disk through a Storage Area Network (SAN) controller, and the average read/write speed of the hard disk is calculated by sending a large number of data read/write requests to the hard disk by the software tool CRYSTALDISKMARK for testing the performance of the hard disk, and measuring the speed at which the hard disk completes the requests within a certain period of time.

The device temperature refers to an average temperature of hardware devices of each link node.

It should be understood that the data transmission cumulative byte number may be obtained by capturing a network data packet through a network protocol analysis tool Wireshark and calculating the data average transmission rate according to the size and the number of the data packet, and the data average transmission rate may be calculated by sending test data to a server through a network speed test tool SPEEDTEST and measuring a response time.

It should also be understood that the data packet loss rate may be calculated by performing a packet loss rate test using a network performance test tool.

It should be noted that, the bandwidth usage rate of the network interface refers to a ratio of an actual data amount transmitted by the network interface in a unit time to a theoretical maximum transmission data amount, reflecting usage efficiency of the network interface,

In this embodiment, the analyzing the comprehensive load evaluation index value of each link node specifically includes analyzing and processing to obtain a hardware operation load index of each link node based on a hardware performance parameter.

In this embodiment, the specific analysis process of the hardware operation load index of each link node is as follows, and the specific analysis process includes extracting reference hardware performance parameters stored in a database, where the reference hardware performance parameters include a reference CPU usage rate, a reference memory occupancy rate, a reference consumption speed of a hard disk storage capacity, a reference read-write speed of the hard disk, and a reference temperature of the device.

The database is configured to store reference index data, where the reference index data includes first reference index data, second reference index data, and third reference index data.

The first reference index data comprises a reference hardware performance parameter and a reference data transmission parameter, and also comprises the number of redundant backup nodes corresponding to each capacity expansion reference value interval and the reference load data of the redundant backup nodes, and also comprises an operation load index threshold value and a redundant backup node use load index threshold value.

The second reference index data comprises a CPU (Central processing Unit) use rate weight, a memory occupancy weight, a hard disk storage capacity consumption speed weight, a hard disk average read-write speed weight and a device temperature weight, and also comprises a data transmission accumulated byte number weight, a data average transmission speed weight, an accumulated transmission data quantity weight, a data packet loss rate weight and a network interface bandwidth use rate weight.

The third reference index data comprises a hardware operation load index weight and a data transmission load index weight, and also comprises an access frequency weight, a maximum connection number weight and an average read-write operation rate weight.

In a specific embodiment, the hardware operation load index of each link node has the following specific formula:

,

Wherein, the The load index is run for the hardware of the i-th link node,CPU utilization for the ith link node,In order to refer to the CPU utilization rate,For the memory occupancy of the ith link node,For the purpose of reference to the memory occupancy rate,The hard disk storage capacity consumption rate for the i-th link node,The consumption speed is referenced for the storage capacity of the hard disk,The average read-write speed of the hard disk of the ith link node,For the reference read-write speed of the hard disk,For the device temperature of the ith link node,For the reference temperature of the device,For the CPU to use the rate weight value,As the weight value of the occupancy rate of the memory,For the hard disk storage capacity consumption rate weight,The weight value of the average read-write speed of the hard disk,I is the number of each link node for the equipment temperature weight,M is the number of link nodes and e is a natural constant.

It should be noted that, the value of the CPU usage weight ranges from 0 to 1, in this embodiment, the CPU usage weight is a value of a preset CPU usage weight in the database, which indicates the influence degree of the CPU usage on the hardware running load index of the link node, and when in use, the preset CPU usage weight may be directly obtained from the database, and the corresponding relationship may be a preset mapping relationship, for example, the node CPU usage and the preset CPU usage weight 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, where the mapping relationship is one-to-one correspondence.

It should be noted that, the memory occupancy rate weight ranges from 0 to 1, in this embodiment, the memory occupancy rate weight is a preset memory occupancy rate weight in the database, and represents a value of the influence degree of the memory occupancy rate on the hardware running load index of the link node, when in use, the preset memory occupancy rate weight can be directly obtained from the database, and the corresponding relationship can be a preset mapping relationship, for example, the node memory occupancy rate and the preset memory occupancy rate weight in the database form a mapping set, and the real-time memory occupancy rate is input into the mapping set to obtain the memory occupancy rate weight, where the mapping relationship is one-to-one correspondence.

It should be noted that, the value range of the weight value of the hard disk storage capacity consumption speed is between 0 and 1, in this embodiment, the weight value of the hard disk storage capacity consumption speed is a preset weight value of the hard disk storage capacity consumption speed in the database, the value of the influence degree of the hard disk storage capacity consumption speed on the hardware running load index of the link node is indicated, when in use, the preset weight value of the hard disk storage capacity consumption speed can be directly obtained from the database, the corresponding relationship of the weight value of the hard disk storage capacity consumption speed can be a preset mapping relationship, for example, the node hard disk storage capacity consumption speed and the preset weight value of the hard disk storage capacity consumption speed 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 weight value of the hard disk storage capacity consumption speed.

It should be noted that, the average read-write speed weight of the hard disk is in a range of 0 to 1, in this embodiment, the average read-write speed weight of the hard disk is a preset average read-write speed weight of the hard disk in the database, which indicates a value of an influence degree of the average read-write speed of the hard disk on the hardware running load index of the link node, and when in use, the preset average read-write speed weight of the hard disk can be directly obtained from the database, and the corresponding relationship of the preset average read-write speed weight of the hard disk can be a preset mapping relationship, for example, the average read-write speed of the node hard disk and the preset average read-write speed weight of the hard disk in the database form a mapping set, and the real-time average read-write speed of the hard disk is input into the mapping set to obtain the average read-write speed weight of the hard disk, where the mapping relationship is one-to-one.

It should be noted that, the value of the equipment temperature weight ranges from 0 to 1, in this embodiment, the equipment temperature weight is a preset equipment temperature weight in the database, and represents a value of the influence degree of the equipment temperature on the hardware operation load index of the link node, when in use, the preset equipment temperature weight can be directly obtained from the database, and the corresponding relationship of the preset equipment temperature weight can be a preset mapping relationship, for example, the node equipment temperature and the preset equipment temperature weight in the database form a mapping set, and the real-time equipment temperature is input into the mapping set to obtain the equipment temperature weight, where the mapping relationship is one-to-one correspondence.

It should be further noted that, in this embodiment, the hardware operation load index of each link node is obtained by processing according to the CPU usage rate, the memory occupancy rate, the hard disk storage capacity consumption speed, the hard disk average read-write speed and the device temperature, so that, for example, when the CPU usage rate of a certain link node is high, it means that the CPU of the certain link node is performing a large number of operation tasks, its processing capacity faces a large pressure, if the memory occupancy rate is also high at this time, the superposition of the two may cause serious degradation of the system performance, because the high memory occupancy rate may cause the CPU to encounter a bottleneck in the data exchange and storage process, thereby further increasing the hardware operation load, and if the hard disk storage capacity consumption speed is low at this time, this may alleviate the pressure of the whole hardware to a certain extent, because the lower consumption speed of the storage capacity of the hard disk means that the system has relatively fewer read-write operations on the hard disk, the hard disk can have more resources to respond to the requests of other hardware components, when the average read-write speed of the hard disk is higher, even if the CPU utilization rate and the memory occupancy rate are higher, the hard disk can rapidly respond to the read-write requests of data, and provide the needed data for the CPU and the memory, so that the overall pressure of the hardware operation is relieved to a certain extent, otherwise, if the average read-write speed of the hard disk is lower, the CPU utilization rate and the memory occupancy rate can become the bottleneck of the whole hardware system under the condition that the CPU utilization rate and the memory occupancy rate are higher, if the equipment temperature is increased, the CPU is possibly reduced in frequency or throttled to prevent overheating, thereby leading to the reduction of the CPU utilization rate, because the CPU processing capacity is reduced, the same load cannot be processed, and the high temperature can influence the stability and the performance of the memory, meanwhile, the temperature of the hard disk is increased to possibly influence the read-write performance of the hard disk, so that the average read-write speed of the hard disk is reduced, if the system tries to perform a large number of I/O operations at high temperature, the consumption of the storage capacity of the hard disk is possibly accelerated, the average read-write speed of the hard disk is reduced, the hardware operation load index obtained by comprehensively considering the parameters can more comprehensively reflect the actual operation condition and the pressure bearing capacity of the hardware of the link node, when the hardware operation load index of a certain link node is higher, the adverse result that the factors are mutually overlapped can be possibly caused, deep analysis and comprehensive optimization measures are needed to ensure that the hardware of the link node can stably and efficiently operate, the reliability and the performance of the whole system are improved, and the hardware fault risk is avoided.

In a specific embodiment, by analyzing the hardware operation load index of each link node, the hardware operation efficiency and pressure condition of each key node in the medical alliance link system can be effectively measured and controlled, and a powerful support is provided for stable operation and optimization upgrading of the system.

In this embodiment, the data transmission load index of each link node is specifically analyzed by extracting reference data transmission parameters stored in a database, where the reference data transmission parameters include a reference data transmission cumulative byte number, a reference data average transmission rate, a reference cumulative transmission data amount, a reference data packet loss rate, and a reference network interface bandwidth usage rate.

In a specific embodiment, the data transmission load index of each link node has the following specific formula:

,

Wherein, the The data transmission load index for the ith link node,The number of bytes is accumulated for the data transmission of the ith link node,The number of bytes is accumulated for the reference data transmission,For the data average transmission rate of the ith link node,For the reference data average transmission rate,For the accumulated amount of transmission data of the i-th link node,For reference to the accumulated amount of transmission data,For the data packet loss rate of the ith link node,For the reference data packet loss rate,Network interface bandwidth usage for the ith link node,To reference the network interface bandwidth usage,The byte number weights are accumulated for the data transmission,As the weight of the average transmission rate of the data,In order to accumulate the weight of the amount of data transmitted,As the weight value of the packet loss rate of the data,For the network interface bandwidth usage weights, i is the number of each link node,M is the number of link nodes and e is a natural constant.

It should be noted that, the value of the data transmission cumulative byte number weight ranges from 0 to 1, in this embodiment, the data transmission cumulative byte number weight is a value of a preset data transmission cumulative byte number weight in the database, which represents the influence degree of the data transmission cumulative byte number on the data transmission load index of the link node, and when in use, the preset data transmission cumulative byte number weight can be directly obtained from the database, and the corresponding relationship can be a preset mapping relationship, for example, the node data transmission cumulative byte number and the preset data transmission cumulative byte number weight in the database form a mapping set, and the real-time data transmission cumulative byte number is input into the mapping set to obtain the data transmission cumulative byte number weight, where the mapping relationship is one-to-one correspondence.

It should be noted that, the value of the data average transmission rate weight ranges from 0 to 1, in this embodiment, the data average transmission rate weight is a preset data average transmission rate weight in the database, and indicates a value of the influence degree of the data average transmission rate on the data transmission load index of the link node, when in use, the preset data average transmission rate weight can be directly obtained from the database, and the corresponding relationship can be a preset 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, where the mapping relationship is one-to-one correspondence.

It should be noted that, the value of the cumulative transmission data amount weight ranges from 0 to 1, in this embodiment, the cumulative transmission data amount weight is a preset cumulative transmission data amount weight in the database, and represents a value of the influence degree of the cumulative transmission data amount on the data transmission load index of the link node, when in use, the preset cumulative transmission data amount weight can be directly obtained from the database, and the corresponding relationship can be a preset mapping relationship, for example, the node cumulative transmission data amount and the preset cumulative transmission data amount weight in the database form a mapping set, and the real-time cumulative transmission data amount is input into the mapping set to obtain the cumulative transmission data amount weight, where the mapping relationship is one-to-one correspondence.

It should be noted that, the value of the data packet loss rate weight ranges from 0 to 1, in this embodiment, the data packet loss rate weight is a preset data packet loss rate weight in the database, and indicates a value of the influence degree of the data packet loss rate on the data transmission load index of the link node, when in use, the preset data packet loss rate weight can be directly obtained from the database, and the corresponding relationship can be a preset mapping relationship, for example, the node data packet loss rate and the preset data packet loss rate weight 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, where the mapping relationship is one-to-one correspondence.

It should be noted that, the value range of the network interface bandwidth usage weight value is between 0 and 1, in this embodiment, the network interface bandwidth usage weight value is a value of the degree of influence of the network interface bandwidth usage weight value on the data transmission load index of the link node, where the value indicates the degree of influence of the network interface bandwidth usage weight value on the data transmission load index of the link node, and when in use, the preset network interface bandwidth usage weight value may be directly obtained from the database, and the corresponding relationship may be a preset mapping relationship, for example, the node network interface bandwidth usage weight value and the preset network interface bandwidth usage weight value in the database form a mapping set, and the real-time network interface bandwidth usage weight value is input into the mapping set to obtain the network interface bandwidth usage weight value, where the mapping relationship is one-to-one correspondence.

It should be further noted that, in this embodiment, the data transmission load index of each link node is obtained by processing according to the number of accumulated bytes of data transmission, the average data transmission rate, the accumulated data transmission amount, the data packet loss rate and the bandwidth utilization rate of the network interface, which considers the mutual influence of these parameters, for example, when the number of accumulated bytes of data transmission of a certain link node is higher, this means that the node has already transmitted a large amount of data within a period of time, which shows that the node bears a large load on the scale of the data transmission task, if the data average transmission rate is low, this indicates that the data transmission efficiency is relatively low, a large amount of data accumulation waits for transmission, so that the node may face difficulties in processing the subsequent data transmission task, such as overflow of a data buffer area, backlog, and the like, and thus may cause increase of delay and instability of data transmission, when the data average transmission rate is high, even if the number of accumulated bytes of data transmission is large, this may rapidly complete the data transmission task, thereby relieving the problem that the data transmission task is relieved to a certain extent, this may cause a large amount of data loss only when the data transmission is not always required to be more frequently initiated, and the data transmission mechanism is not frequently lost, if the data transmission is more frequently has been required, and the data transmission can be only lost, which causes the problem in the current transmission of the data transmission mechanism is more frequently occurs, and the data transmission can be more frequently caused if the data transmission can be only has been lost, but is more frequently transmitted in the data transmission time can be caused, further increasing the load of data transmission and the load of nodes, the increase of the bandwidth utilization means that more data is transmitted through the network interface, so that the number of accumulated bytes of data transmission also increases, the increase of the bandwidth utilization may also cause network congestion, further affecting the average rate of data transmission, if the network interface approaches its maximum bandwidth, new data packets may be queued for transmission, which may reduce the average transmission rate of data, and at the same time, when the bandwidth utilization of the network interface reaches or approaches the maximum, the new data packets may be discarded because of insufficient bandwidth resources, thereby causing the increase of the packet loss rate. The data transmission load index obtained by comprehensively considering the parameters can more comprehensively reflect the actual working state and the pressure bearing capacity of the link node in terms of data transmission, when the data transmission load index of a certain link node is higher, the adverse results of mutual superposition of the factors possibly occur, deep analysis is needed, comprehensive optimization measures are adopted, so that the link node can be ensured to stably and efficiently perform data transmission, the reliability and the performance of the whole network system are improved, and the fault risk is avoided.

In a specific embodiment, by analyzing the data transmission load index of each link node, the operation pressure of the link node in the data transmission link can be accurately reflected, accurate guidance is provided for reasonable allocation of resources, fine network management is facilitated, key data support and decision basis are provided for fine network management of a medical alliance chain, and digital construction of the medical industry is promoted to advance to a higher level.

In a specific embodiment, the specific formula of the comprehensive load evaluation index value of each link node is as follows:

It should be noted that, the value range of the hardware operation load index weight is between 0 and 1, in this embodiment, the hardware operation load index weight is a preset hardware operation load index weight in the database, and indicates a value of the influence degree of the hardware operation load index on the operation load index of the link node, when in use, the preset hardware operation load index weight can be directly obtained from the database, and the corresponding relationship of the preset hardware operation load index weight can be a preset mapping relationship, for example, the node hardware operation load index and the preset hardware operation load index weight 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, where the mapping relationship is one-to-one correspondence.

It should be noted that, the value of the data transmission load index weight ranges from 0 to 1, in this embodiment, the data transmission load index weight is a preset data transmission load index weight in the database, and indicates a value of the influence degree of the data transmission load index on the operation load index of the link node, when in use, the preset data transmission load index weight can be directly obtained from the database, and the corresponding relationship can be a preset mapping relationship, for example, the node data transmission load index and the preset data transmission load index weight 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, where the mapping relationship is one-to-one correspondence.

It should be further noted that, in this embodiment, the comprehensive load assessment index value of each link node is obtained by processing according to the hardware operation load index of each link node and the data transmission load index of each link node, which considers the mutual influence between these parameters, for example, when the hardware operation load index of a certain link node is higher, it means that the hardware device of the node faces a larger pressure when processing tasks, the CPU usage rate may be close to saturation, the memory occupancy rate is higher, or the read-write frequency of the storage device approaches the limit, etc., if the data transmission load index is lower at this time, i.e. the data inflow and outflow amount of the node is relatively smaller, the frequency and scale of the data transmission are in the bearable range, this can alleviate the overall operation pressure to a certain extent, because the lower data transmission load will not further burden of hardware, the hardware can have more residual force to cope with the current tasks, however, when the data transmission load index is higher, it means that the link node needs to frequently receive, process and send a large amount of data when the hardware operation load index is also at a higher level, the node may be at this time, or the CPU may be in a higher level, or the read-write frequency approaches the limit, etc., if the data transmission load index is higher, the node may be in a higher level, such as a high load may cause a high latency, and the data transmission load may be high, and the hardware may have a high latency load may be caused by the buffer memory has been required to wait, and the high, and the data transmission has been in a high latency condition, and has been waiting for the high load of the data transmission load, and has been high latency, and has been waiting for a high data transmission load, and has been high latency, and has been due to a high data transmission load is high, and has high performance is due to a high performance, and has high performance can and has high quality, or a single-point bottleneck occurs on some key hardware components, for example, a network interface may overheat or have errors due to a large amount of data transmission, so that the quality and stability of the data transmission are affected, and the link node operation load index obtained by comprehensively considering the parameters can reflect the actual operation condition and the pressure bearing capacity of the node more comprehensively, so that the link node can operate stably and efficiently, the reliability of the whole alliance chain is improved, and the fault risk is avoided.

Referring to fig. 2, a graph of a relation between a link node data transmission load index and a link node operation load index according to an embodiment of the present invention is shown, where the abscissa is the link node data transmission load index, and the ordinate is the link node operation load index corresponding to the link node data transmission load index according to the embodiment, and as the data transmission load index increases, it can be obviously seen from the graph that the link node operation load index generally increases, because when the data transmission load index increases, the link node operation pressure increases, however, the distribution of the dispersion points does not show a strict linear relation, but rather has a certain discreteness, which reflects that in an actual operation environment, besides the factor of the data transmission load index, there are other factors that affect the link node operation load index, when the data transmission load index of the link node increases, it may mean that the node needs to process more data flow and more frequent data interaction tasks, which can actually increase the operation pressure of the link node operation load index, and further increase the operation load index, but because the load of hardware is increased, and the load of the node operation load index can be even more significantly reduced, even if the load of the hardware is increased, and the hardware can be significantly reduced, even if the load is significantly, and the load of the hardware can be significantly increased, even if the load is not is increased, and the hardware can be significantly, and the load can be significantly is significantly reduced.

In a specific embodiment, by analyzing the comprehensive load evaluation index value of each link node, the operation efficiency and the pressure condition of each link node in the medical alliance link system can be effectively evaluated and mastered, a solid foundation is provided for the optimization and the stable operation of the system, meanwhile, a clear direction is provided for the reasonable allocation of resources, and the dynamic and accurate management of the medical alliance link system is facilitated.

And S3, based on 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, and generating operation load evaluation labels of each link node.

In this embodiment, the generating the operation load evaluation label of each link node specifically includes generating the operation load evaluation label of each link node by comparing according to the comprehensive load evaluation index value of each link node and a preset operation load index threshold value.

It should be understood that the operation load index threshold refers to a key reference value stored in the database and used for measuring whether the operation load state of the link node is in a reasonable range, the operation load index threshold is set based on long-term operation monitoring and performance analysis of the medical alliance link system and combines the actual requirement of medical service and the bearing capacity of system resources, and whether the operation load of the link node is in a normal range can be rapidly judged by comparing the comprehensive load evaluation index value of each link node with the operation load index threshold.

In a specific embodiment, by generating the operation load evaluation labels of all the link nodes and configuring node backup resources based on the operation load evaluation labels, convenience and pertinence of management are improved, long-term performance monitoring and trend analysis are facilitated, potential performance problems and trend rules can be found through tracking and recording the evaluation label changes of all the link nodes in different time periods, and sustainable development and stable operation of the medical alliance chain system are ensured.

In this embodiment, the processing obtains the number of redundant backup nodes of each link node, and specifically includes the steps of based on an operation load evaluation label of each link node, defining the number of redundant backup nodes of a certain link node as zero if the operation load evaluation label of the certain link node is a normal operation load, and marking the link node as a demand expansion link node if the operation load evaluation label of the certain link node is an abnormal operation load, thereby counting each demand expansion link node.

In a specific embodiment, the reliability and stability of the system are remarkably enhanced by analyzing the number of redundant backup nodes of each link node, and the redundant backup nodes can be rapidly started to replace the main link node when the main link node fails or fails to work normally under high load pressure by accurately calculating and configuring the number of the redundant backup nodes, so that the transmission and processing of medical data are not interrupted, the expandability and the adaptability of the system are improved, the safety of the whole medical alliance chain is improved, the risk of data loss and leakage can be reduced by reasonably distributing the redundant backup nodes, and a powerful guarantee is provided for information safety.

The resource allocation of each link node may be performed by a server management console.

The server management console is core equipment for carrying out link node resource allocation, and is usually built based on open source server management software, hardware resources of a server node can be directly allocated and managed through the server management console, in a specific embodiment, parameters such as the number of cores, main frequency, power management mode and the like of a CPU (Central processing Unit) can be adjusted in the console for allocation of CPU resources, for example, on a certain hospital node server of a medical alliance chain, if CPU load is too high during transcoding tasks of processing a large amount of medical image data, some CPU cores on other idle servers can be dynamically allocated to the node server through the console, so that data processing capacity of the node server is improved.

For the configuration of the memory resources, memory banks can be added or removed in the console, the allocation strategy of the memory is adjusted, such as setting the memory buffer size, the use mode of the virtual memory, and the like, for example, when the medical scientific research institution node performs large-scale data analysis, it is found that the data processing speed is slow due to insufficient memory, and more memory banks can be added or the use mode of the memory is optimized through the server management console, so that more memory is allocated to the key data processing process.

In this embodiment, the method for configuring dynamic security resources of a medical alliance chain further includes the step of configuring dynamic security resources of redundant backup nodes, and the specific process is that based on the number of the redundant backup nodes of each link node, each redundant backup node is counted.

It should be noted that, with the access frequency, the data packet capturing may be performed by using the Wireshark, and the filter is set to display only the data packets related to the target redundant backup node, and then the access frequency is calculated according to the number of captured data packets and the time span.

And the maximum number of connected people can be obtained by using network management software to check the number of users connected with the node.

The average read-write operation rate can be obtained by testing the read-write speed through CRYSTALDISKMARK tools and calculating the average value of the read-write operation rate in a preset period.

And comparing the usage load index of each redundant backup node with a redundant backup node usage load index threshold stored in a database, if the usage load index of a certain redundant backup node is smaller than or equal to the redundant backup node usage load index threshold, not performing storage resource configuration on the redundant backup node, and if the usage load index of a certain redundant backup node is larger than the redundant backup node usage load index threshold, performing storage resource configuration on the redundant backup node with preset storage capacity.

It should be understood that, the configuring storage resources of the redundant backup node may perform preset storage capacity allocation through a storage management interface provided by the computer operating system, map the allocated storage resources to the redundant backup node through a network storage protocol, such as iSCSI, and install a corresponding storage driver and a configuration file, such as a remote management tool SSH, on the redundant backup node to identify and use the newly allocated storage resources.

In a specific embodiment, the load index is used by each redundant backup node, and the specific formula is as follows:

It should be noted that, the access frequency weight ranges from 0 to 1, in this embodiment, the access frequency weight is a preset access frequency weight in the database, and indicates a value of the influence degree of the access frequency on the load index of the redundant backup node, and when in use, the preset access frequency weight may be directly obtained from the database, where the corresponding relationship may be a preset mapping relationship, for example, the node access frequency and the preset access frequency weight in the database form a mapping set, and the real-time access frequency input mapping set is used to obtain the access frequency weight, where the mapping relationship is one-to-one correspondence.

It should be noted that, the maximum number of connected people weight ranges from 0 to 1, in this embodiment, the maximum number of connected people weight is a preset maximum number of connected people weight in the database, and indicates a value of an influence degree of the maximum number of connected people on the load index used by the redundant backup node, when in use, the preset maximum number of connected people weight can be directly obtained from the database, and the corresponding relationship can be a preset mapping relationship, for example, the maximum number of connected people of a node and the preset maximum number of connected people weight in the database form a mapping set, and the real-time maximum number of connected people is input into the mapping set to obtain the maximum number of connected people weight, where the mapping relationship is one-to-one correspondence.

It should be noted that, the average read-write operation rate weight ranges from 0 to 1, in this embodiment, the average read-write operation rate weight is a preset average read-write operation rate weight in the database, and indicates a value of an influence degree of the average read-write operation rate on the use load index of the redundant backup node, when in use, the preset average read-write operation rate weight can be directly obtained from the database, and the corresponding relationship can be a preset mapping relationship, for example, the node average read-write operation rate and the preset average read-write operation rate weight in the database form a mapping set, and the real-time average read-write operation rate is input into the mapping set to obtain the average read-write operation rate weight, where the mapping relationship is one-to-one correspondence.

It should be further noted that, in this embodiment, the usage load index of each redundant backup node is obtained by processing according to the usage access frequency of each redundant backup node, the maximum number of connections, and the average read-write operation rate, which considers the mutual influence between these parameters, for example, when the usage access frequency of a certain redundant backup node is higher, this means that the number of times the node is requested to be served in unit time is greater, this shows that the node assumes more frequent tasks in terms of data interaction, the load pressure is relatively greater at the access level, if the maximum number of connections is lower at this time, it is shown that the number of devices or users that establish connections with the node at the same time is smaller, this alleviates the overall load pressure to a certain extent, because the number of connections is smaller, which means that the concurrency of system resources is relatively less, and the concurrent demand for data processing and transmission is also relatively lower, when the average read-write operation rate is faster, the node can rapidly process the read-write request of data, even if the access frequency and the maximum number of connections are higher, this node can also respond efficiently, thereby alleviating the load pressure is reduced to a certain extent, the load is relatively less, and the average number of devices or users that can respond to the data is more rapidly broken when the average connection is higher, and the average number of connections is higher than the average, and the data is more than the data processing is required to be more than the network, and the data processing is more easily broken, and the data processing is more than the network is able, and the node can respond to the data and has higher than the high latency and has high performance and higher than the performance and higher when the overall load and has high performance. The actual working state and load bearing capacity of the node can be comprehensively reflected, when the use load index of a certain redundant backup node is higher, the adverse result that the factors are mutually overlapped is likely, deep analysis is needed, comprehensive optimization measures are adopted to carry out resource allocation, so that the redundant backup node can stably and efficiently operate, the reliability and performance of the whole system are improved, and the fault risk is avoided.

Taking 4 groups of different redundant backup nodes as an example in the embodiment, when the average read-write operation rate of the 4 groups of redundant backup nodes is 80 kilobytes per second, the reference access frequency is defined as 50 times per minute, the maximum connection number is defined as 100 people, the reference average read-write operation rate is defined as 100 kilobytes per second, the access frequency weight is defined as 0.35, the maximum connection number weight is defined as 0.4, the average read-write operation rate weight is defined as 0.25, and the load index of the redundant backup nodes obtained through processing is as follows based on the difference between the access frequency and the maximum connection number:

table 1 redundant backup node uses load index:

Group of	Using access frequency	Maximum number of people connected	Redundant backup node usage load index
				First group of	20	70	1.87
Second group of	40	90	2.01
				Third group of	60	110	2.16
Fourth group	80	130	2.32

;

In combination with the above table, the usage load index of the fourth redundant backup node is the highest, which indicates that the operation pressure faced by the fourth redundant backup node is the most prominent compared with other groups, and in a specific example, for the redundant backup node with higher usage access frequency and maximum number of connected people, the complexity of data processing and the pressure born by system resource allocation are both relatively high, which means that the related resources need to be optimally allocated to ensure that the redundant backup node can operate stably and efficiently.

In a specific embodiment, by analyzing the usage load index of each redundant backup node, it can clearly indicate which redundant backup nodes are bearing larger working pressure, providing accurate basis for reasonable allocation and dynamic adjustment of resources, being beneficial to realizing fine system maintenance and management, and providing reliable guarantee for stable operation and data security of medical alliance chain system.

In a specific embodiment, by providing a dynamic safety resource allocation method for a medical alliance chain, accurate allocation of resources of the medical alliance chain system is realized, a resource allocation strategy and an enabling mechanism of a redundant backup node 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.

It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.

The preferred embodiments of the invention disclosed above are intended only to assist in the explanation of the invention. The preferred embodiments are not exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best understand and utilize the invention and are intended to be within the scope of the invention without departing from the spirit and scope of the invention.

Claims

1. A dynamic safety resource allocation method for a medical alliance chain is characterized by comprising the following steps:

s1, counting a plurality of nodes in a medical alliance chain link point network architecture, and marking the nodes as all link nodes;

S4, according to the operation load evaluation labels of the link nodes, the number of redundant backup nodes of the link nodes is obtained through processing, and resource allocation of the link nodes is carried out;

the method also comprises the steps of carrying out dynamic safety resource allocation on the redundant backup node, wherein the specific process is as follows:

based on the number of redundant backup nodes of each link node, counting each redundant backup node;

Sensing and monitoring each redundant backup node in a preset configuration period to obtain service load data of each redundant backup node, wherein the service load data specifically comprises service access frequency, maximum number of connected people and average read-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 comprises reference use access frequency, reference maximum number of connection persons and reference average read-write operation rate;

analyzing and processing based on the use load data of each redundant backup node and the reference load data of the redundant backup node to obtain the use load index of each redundant backup node, wherein the use load index of each redundant backup node is a numerical result for quantifying the use load data of each redundant backup node and the reference load data of the redundant backup node and is used for representing the use load degree of each redundant backup node;

Comparing the usage load index of each redundant backup node with a usage load index threshold of the redundant backup node, if the usage load index of a certain redundant backup node is smaller than or equal to the usage load index threshold of the redundant backup node, not performing storage resource configuration on the redundant backup node, and if the usage load index of a certain redundant backup node is larger than the usage load index threshold of the redundant backup node, performing storage resource configuration on the redundant backup node with preset storage capacity;

the redundant backup nodes use load indexes, and the specific formulas are as follows:

,

Wherein, the The load index is used for the jth redundant backup node,The access frequency is used for the jth redundant backup node,For reference purposes the access frequency is used,The maximum number of connections for the jth redundant backup node,For reference to the maximum number of people connected,The jth redundant backup node averages the read and write operation rates,To refer to the average read-write operation rate,In order to use the access frequency weight value,For the weight value of the maximum number of connected people,For the average read-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.

2. The method for configuring dynamic safety resources of medical alliance chain according to claim 1, wherein the monitoring of the operation state of each link node comprises the following specific monitoring process:

monitoring the running state of each link node based on a preset dynamic monitoring frequency in a preset dynamic monitoring period to acquire the running state data of each link node, wherein the running state data of each link node comprises hardware performance parameters and data transmission parameters;

the hardware performance parameters comprise CPU utilization rate, memory occupancy rate, hard disk storage capacity consumption speed, hard disk average read-write speed and equipment temperature of each link node in a dynamic monitoring period;

3. The method for configuring dynamic safety resources of medical alliance chain according to claim 2, wherein the analyzing the comprehensive load evaluation index value of each link node comprises the following specific analysis process:

based on the hardware performance parameters, analyzing and processing to obtain the hardware operation load index of each link node;

Based on the data transmission parameters, analyzing and processing to obtain the data transmission load index of each link node;

According to the hardware operation load index of each link node and the data transmission load index of each link node, comprehensively analyzing and processing to obtain comprehensive load evaluation index values of each link node;

4. The method for configuring dynamic safety resources of medical alliance chain according to claim 3, wherein the hardware operation load index of each link node comprises the following specific analysis process:

extracting reference hardware performance parameters stored in a database, wherein the reference hardware performance parameters comprise reference CPU utilization rate, reference memory occupancy rate, hard disk storage capacity reference consumption speed, hard disk reference read-write speed and equipment reference temperature;

According to the hardware performance parameters and the reference hardware performance parameters, analyzing and processing to obtain the hardware operation load index of each link node;

5. The method for configuring dynamic safety resources of medical alliance chain according to claim 3, wherein the data transmission load index of each link node comprises the following specific analysis process:

Extracting reference data transmission parameters stored in a database, wherein the reference data transmission parameters comprise reference data transmission accumulated byte number, reference data average transmission rate, reference accumulated transmission data quantity, reference data packet loss rate and reference network interface bandwidth utilization rate;

According to the data transmission parameters and the reference data transmission parameters, analyzing and processing to obtain data transmission load indexes of all the link nodes;

6. The method for configuring dynamic safety resources of medical alliance chains according to claim 1, wherein the method for generating the operation load evaluation labels of the link nodes is characterized by comprising the following specific processes:

Generating operation load evaluation labels of all the link nodes by comparing according to the comprehensive load evaluation index values of all the link nodes and a preset operation load index threshold value;

the operation load evaluation tag comprises a normal operation load and an abnormal operation load;

If the operation load index of a certain link node is lower than or equal to a preset operation load index threshold value, defining an operation load evaluation label of the link node as a normal operation load;

7. The method for configuring dynamic safety resources of medical alliance chain according to claim 6, wherein 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 labels of all the link nodes, if the operation load evaluation label of a certain link node is a normal operation load, defining the number of redundant backup nodes of the link node as zero, and if the operation load evaluation label of a certain link node is an abnormal operation load, marking the link node as a demand expansion link node, thereby counting all the demand expansion link nodes;

8. The method for configuring dynamic safety resources of medical alliance chain according to claim 3, wherein the comprehensive load evaluation index value of each link node has the following specific formula:

,

Wherein, the An index value is evaluated for the integrated load of the i-th link node,The load index is run for the hardware of the i-th link node,The data transmission load index for the ith link node,For the hardware to run the load index weight,The load index weight for data transmission, i is the number of each link node,M is the number of link nodes.