WO2020134133A1

WO2020134133A1 - Resource allocation method, substation, and computer-readable storage medium

Info

Publication number: WO2020134133A1
Application number: PCT/CN2019/102467
Authority: WO
Inventors: 高昇宇; 韦磊; 朱红; 李维; 李秋生; 蒋承伶; 严东; 蒋陵; 陈殿欣; 邵明驰; 郭闯; 陈旸羚; 徐思雅; 郭少勇; 喻鹏
Original assignee: 国网江苏省电力有限公司南京供电分公司; 国网江苏省电力有限公司; 北京邮电大学
Priority date: 2018-12-27
Filing date: 2019-08-26
Publication date: 2020-07-02
Also published as: CN109639498B; CN109639498A

Abstract

A resource allocation method, a substation, and a computer-readable storage medium. The method comprises: receiving multiple service requests; calculating a service area of each service, and checking a service reliability requirement of each service; sequentially selecting, in a descending order of the service reliability requirement, a candidate resource allocation scheme for each service according to the service area of each of multiple services, and forming a set P; selecting, according to a resource allocation model, a candidate resource allocation scheme having the smallest MOI value from the set P, and allocating a resource according to the selected scheme; if the selected scheme does not meet the service reliability requirement and other candidate resource allocation schemes are available, updating the set P as the other candidate resource allocation schemes, and returning to performing selection of a candidate resource allocation scheme having the smallest MOI value; and if no other candidate resource allocation scheme is available, recalculating a service area, re-selecting backup resource allocation schemes for each service, updating the set P as the re-selected backup resource allocation schemes, and returning to performing selection of a resource allocation scheme having the smallest MOI value.

Description

Resource configuration method, substation and computer readable storage medium

This application requires the priority of the Chinese patent application with the application number 201811609272.6 filed by the China Patent Office on December 27, 2018. The entire contents of this application are incorporated by reference in this application.

Technical field

This application belongs to the technical field of power grid security, for example, it relates to network equipment of a substation communication system, such as a resource configuration method, a substation, and a computer-readable storage medium.

Background technique

As the degree of intelligence of substations continues to increase, more and more types of services need to be accessed in substations. These phenomena have put forward new demands for the flexibility, efficiency and economy of smart substations. However, in the intelligent substation communication architecture, the network equipment itself is highly integrated with hardware and software, and can only complete specific functions in specific scenarios, forming its own integrated system. To ensure the availability of services, substations will deploy a sufficient number of devices to support large-capacity business flows. However, the business volume is not constant. Therefore, many of these devices will be idle when the network is idle, resulting in high deployment costs of substations and low resource utilization. Therefore, how to break the barriers between dedicated hardware devices, allocate resources flexibly, optimize costs while ensuring service quality, and maintain the normal operation of substations is an urgent problem to be solved.

Summary of the invention

The present application provides a resource configuration method, substation, and computer-readable storage medium to flexibly adapt to various business needs, and provide different network functions and security services for various services to improve the utilization rate of shared resources.

The technical solution of this application is as follows: a resource allocation method, based on software defined network (Software Defined Network, SDN) and network function virtualization (Network Function Virtualization, NFV) technology to establish a smart substation resource flexible configuration model, based on the resource flexible configuration model To determine the resource allocation plan by comprehensively studying the cost consumption of the alternatives and the impact on the resource balance of the substation, including the following:

The standard of flexible resource allocation is that the less the cost, the better the balance of resources in the substation. The objective function is to minimize the cost of maintaining the normal operation of the intelligent substation. The terminal equilibrium, business delay, sequence and capacity constraints are the limiting conditions. Resource flexible allocation model:

Among them, MOI stands for importance metric,

Represents the cost of expenditure,

Represents the business balance, χ,

Are the weights of cost and business balance, respectively, s _i represents the ith business,

P _{resi (k)} for the remaining processing capacity of the terminal k, c _{resi (k)} for the remaining storage capacity of the terminal k,; s _i selected service costs resource allocation scheme l _c, b is the service equalization factor

with

Respectively, the processing capacity and storage capacity consumed by the terminal k by the service _si ;

For any embodiment showing the configuration of a link l _c, the remaining bandwidth of the link is not less than the required bandwidth services s _i B _i;

Indicates that the functional sequence in the configuration scheme l _c must be the same as the functional sequence required by the service S _i ,

It means that the link terminal k has the function fg corresponding to the service s _i ;

Is a business delay,

It is the maximum tolerable delay of service S _i ;

In the link representing service s _i , any terminal does not form a cycle; b _k represents the number of services that can be deployed on terminal k;

According to the above model, the resource allocation plan is determined by the following steps:

Step 10: Initialize the use state of the terminal equipment in the intelligent substation, and receive various service requests S.

Step 20: Calculate the service scope of each service in multiple services corresponding to multiple service requests, and check the service reliability requirements of each service.

Step 30: In accordance with the service reliability requirements, from high to low, select an alternative resource configuration scheme for each service according to the service range of each service in the multiple services, and form a set corresponding to each service P.

Step 40: Select an alternative resource configuration scheme with the smallest MOI value in the set P corresponding to each service according to the resource configuration model, and allocate resources according to the selected alternative resource configuration scheme.

Step 50. When the reliability of the alternative resource configuration scheme selected by Step 40 meets the service reliability requirements of each service, go to Step 80. The reliability of the alternative resource configuration scheme selected by Step 40 is not If the service reliability requirements of each service are met, go to Step 60.

Step 60: When there is an alternative resource configuration scheme other than the selected alternative resource configuration scheme in the set P corresponding to each service, update the set P corresponding to each service to the selected one Alternative resource configuration schemes other than the alternative resource configuration schemes and go to Step 40; when there is no alternative resource configuration scheme other than the selected alternative resource configuration scheme in the set P corresponding to each service And go to Step 70.

Step 70: Recalculate the service scope of each business, reselect the alternative resource configuration scheme for each business according to the recalculated service scope of each business, and set the corresponding set P of each business Update to the re-selected alternative resource allocation plan and go to Step 40.

Step 80, end.

This application proposes a terminal balance factor index to measure the balance of equipment resource use. Through comprehensive consideration of the terminal's remaining processing capacity, remaining storage capacity, terminal's remaining in-degree resources, terminal's remaining out-degree resources and total path consumption, a comprehensive quantization of the substation's balance Status; This application has designed an importance measurement index, taking into account both cost and balance factors, so that the resource allocation scheme can meet the goal of ensuring the minimum cost of the substation in a balanced state.

This application proposes a resource allocation scheme based on SDN and NFV technology, which virtualizes resources and uses importance measurement indicators to flexibly configure resources. In the process of flexible resource allocation, with the goal of improving the service quality in the substation, an importance measurement model was established by comprehensively considering the cost and the degree of balance; then, a flexible resource allocation algorithm for service quality was designed for this model. Reflects the resource allocation mechanism and business quality self-inspection mechanism. Simulations show that the algorithm can significantly improve the success rate of business requests, reduce terminal resource consumption, ensure the balanced use of substation resources, and realize long-term sustainable operation of business in the station.

BRIEF DESCRIPTION

FIG. 1 is a flowchart of a resource configuration method provided by an embodiment of this application.

FIG. 2a is the service success rate of the three algorithms in the case where the value of the service provided by the embodiment of the present application in the Poisson distribution arrival state is equal to 1000;

FIG. 2b is the business success rate of the three algorithms in the case that the service provided by the embodiment of the present application has a Poisson distribution and the lambda value is equal to 1500;

FIG. 2c is the service success rate of the three algorithms in the case where the value of the service provided by the embodiment of the present application in the Poisson distribution reaches the value of λ equal to 2000;

FIG. 2d is the service success rate of the three algorithms in the case where the value of the service provided by the embodiment of the present application in the Poisson distribution arrival state is equal to 2500;

FIG. 2e is the business success rate of the three algorithms in the case where the service provided by the embodiment of the present application has a Poisson distribution in a state where the λ value is equal to 3000;

FIG. 2f is the business success rate of the three algorithms provided by the embodiments of the present application at the final stable state under different λ values;

FIG. 3 is a schematic diagram of terminal load balancing factor changes with time provided by an embodiment of the present application;

4 is a schematic diagram of cost comparison provided by an embodiment of the present application.

detailed description

Software-Defined Network (SDN) and Network Function Virtualization (NFV) provide a new idea for this problem. These two technologies introduce the concept of virtualization, decoupling the hardware and functions of dedicated hardware devices, so that business functions no longer depend on the hardware, so that they can be flexibly deployed on general-purpose communication terminals. At this time, the intelligent substation can flexibly allocate resources to the business according to the business needs, ensuring the quality of service. In addition, it can flexibly adjust resource allocation dynamically in scenarios with large and small business volumes, make full use of communication terminal resources, flexibly deploy business functions, and reduce the cost of deploying special equipment.

In order to understand the development status of related technologies, the existing papers and patents were searched, compared and analyzed, and the following technical information with high relevance to this application was selected:

Technical solution 1: "Method and Device for Realizing Flexible Allocation of Business Platform Resources", Patent Publication No. CN104468407A, relates to a method and device for achieving elastic allocation of business platform resources, which is mainly completed in three steps: 1) more cloud resource pools The virtual machines with the same function that participate in load balancing in each service platform are divided into the same virtual machine group; 2) receive the resource usage status of the virtual machine monitored by the integrated network management system; 3) according to the received virtual machine resource usage status and advance The configured virtual machine resource scheduling strategy performs real-time scheduling on or off of virtual machines participating in load balancing in multiple business platforms in the same virtual machine group. This method provides a method for flexibly configuring resources, and realizes resource sharing through multiple business platforms carried in a cloud resource pool.

Technical solution 2: "Multi-service isolation real-time communication system and method for power terminal communication access network", Patent Publication No. CN105207956A, relates to a multi-service isolation real-time communication system and method for power terminal communication access network. The method includes the following two aspects: 1) The system includes an optical line module, multiple optical distribution networks, and multiple optical network units. The optical line module has at least one passive optical network (Passive Optical Network, PON) port, each PON The port is connected to the first optical distribution network, multiple optical distribution networks are connected in series, and each optical distribution network is connected to a corresponding optical network unit; 2) each optical network unit is connected to multiple service terminal devices. This method makes the power system business required by different power safety levels and isolation requirements carried by the same set of communication systems. The logical identification time slot multiplexing mechanism and the logical identification time slot preemption mechanism of the method can ensure the performance requirements of the power system business for real-time and bandwidth communication, so that the real-time performance of the delay-sensitive business can be achieved when the system is fully loaded or overloaded To be guaranteed.

Technical solution 3: "A terminal resource allocation method and terminal equipment", patent publication number CN 106549880 A, to study a terminal resource allocation method and terminal equipment, involving terminal control field. The method includes the following three steps: 1) Obtain the attribute information of the target application to obtain the target attribute information; 2) Determine the target resource allocation plan corresponding to the target application according to the target attribute information; 3) When the target application is running in the foreground, according to the target resource The allocation scheme allocates the system resources of the terminal. The method can set the system resources differently according to the attribute information of the application running in the foreground, and use the system resources reasonably.

In the above solution, technical solution 1 adopts a method and device for elastically allocating resources of the business platform. By dividing the virtual machines with the same function participating in load balancing among multiple business platforms in the cloud resource pool into the same virtual machine group, and Receive the resource usage status of the virtual machine monitored by the integrated network management system, and at the same time, according to the received virtual machine resource usage status and the pre-configured virtual machine resource scheduling strategy, load balancing virtual machines in multiple business platforms in the same virtual machine group Perform real-time scheduling on or off. This method can effectively and flexibly configure resources, but the focus of this method is only on the resource usage of the platform, without considering the service quality factors. Technical solution 2 adopts a multi-service isolation real-time communication system and method for the power terminal communication access network. By designing the system to include an optical line module, multiple optical distribution networks, and multiple optical network units, the optical line module has at least one PON port, each PON port is connected to the first optical distribution network, and multiple optical distribution The networks are connected in series, and each optical distribution network is connected to a corresponding optical network unit. And each optical network unit is connected to multiple service terminal devices. This method enables multiple services to be accessed through a unified terminal. However, the balance of terminal resource usage is not considered. Technical solution 3 adopts a terminal resource allocation method and terminal equipment. By acquiring the attribute information of the target application, the target attribute information is obtained, and then the target resource allocation plan corresponding to the target application is determined according to the information, and finally when the target application runs in the foreground At this time, the system resources of the terminal are allocated according to the target resource allocation scheme. This method can set the system resources differently according to the attribute information of the application running in the foreground, but does not study the optimization and consumption of resources.

Through research, it is found that SDN and NFV technology can realize the separation of hardware and services on general equipment and virtualize network functions. Based on these two technologies, this application establishes a smart substation resource allocation model and defines related problems and objective functions. Based on this idea, it proposes a service quality-oriented flexible resource allocation algorithm, which comprehensively studies the alternatives The cost consumption and the impact on the resource balance of the substation determine the resource allocation plan, and at the same time check the availability of the plan. The resource allocation scheme generated through the importance measure can meet business needs in real time and maintain the stability of substation operation. The implementation of this application will be described below.

1. Establishment of resource allocation model

The goal of the flexible configuration of smart substations is to flexibly configure equipment resources under the premise of ensuring the quality of services, so as to minimize the cost of substations. This application uses MOI (Measure of Importance) as the standard for flexible configuration decisions. The mathematical expression of MOI is

Among them, s _i is the _ith business in the business. the first item

In order to choose the cost of resource allocation plan l _c , the second item b is the business balance, χ,

The weights of cost and business balance respectively. The standard of flexible resource allocation is that the less the cost, the more balanced the resources in the substation, the better.

Now define the following binary variables to represent the network status:

(1) x _j,k =1 indicates that there is a virtual network function VNF named f _j on terminal k, and x _{j,k is} not equal to 1, then there is no virtual network function VNF named f _j on terminal k.

(2) x _i,j,k =1 indicates that the required function f _{j of} service i is placed on terminal k, x _{i,j,k is} not equal to 1, then the required function f _{j of} service i is not placed in Terminal k.

The cost factors that are considered when configuring resources in an intelligent substation include terminal resource costs and path costs. The terminal resource cost is the sum of the processing capacity and storage capacity of the terminal consumed by the service, and the path cost represents the sum of the path resource consumed by the service. The processing power and storage capacity consumed by the terminal k by the service s _i are recorded as

with

Therefore, business s _i chooses the resource allocation plan l _c 's expenditure cost

for

Where n is the number of devices in the link configured by the service s _i , that is, the number of terminals, and B _i is the bandwidth required by the service S _i .

The business balance factor indicates the rationality of the smart substation allocating resources to the business. This factor affects the final resource allocation method. This application uses the remaining processing capacity of the terminal, the remaining storage capacity, the remaining in-degree resources of the terminal, the remaining out-degree resources of the terminal and the total consumption of the path to measure this factor, as follows:

Where p _resi(k) is the remaining processing capacity of terminal k, and c _resi(k) is the remaining storage capacity of terminal k,

Is the remaining in-degree resources of terminal k, that is, the remaining access resources of terminal k,

The remaining resources for terminal k,

The total bandwidth consumed by service s _i . β, ω, and μ are the weight of the remaining capacity of the terminal, the weight of the remaining resource of the terminal, and the weight of the total bandwidth consumed by the service s _i .

In an embodiment, when the reliability of the selected alternative resource solution meets the service reliability requirements of each service, the method further includes: calculating a terminal balance factor to measure the resource balance state after allocating resources. The terminal balance factor represents the resource balance state in the operation state of the intelligent substation, and is used to measure the balance degree after the algorithm is executed in the simulation link. The factor is:

Where α is the weight of the remaining capacity of the terminal, τ is the weight of the remaining bandwidth of the link, and n is the number of terminals.

To ensure the quality of the business, the corresponding service must be provided within the time delay required by the business to ensure the availability of the business. The delay for the smart substation to complete its business is:

among them,

Represents the processing delay of terminal k,

Represents the transmission delay from terminal h to terminal m,

Delay traffic to the terminal S _i k according to the resource allocation.

In summary, this application takes the minimum cost of maintaining the normal operation of smart substations as the objective function, and the terminal equilibrium, business delay, sequence and capacity restrictions as the limiting conditions to obtain a complete mathematical model of flexible resource allocation:

Among them, MOI stands for importance metric,

Represents the cost of expenditure,

Represents the business balance, χ,

Choose the cost of resource allocation scheme l _c for business s _i , and b is the business equilibrium factor;

Is a cost function, p _resi(k) is the remaining processing capacity of terminal k, and c _resi(k) is the remaining storage capacity of terminal k,

with

These are the processing capacity and storage capacity of the terminal k consumed by the service s _i .

For any embodiment showing the configuration of a link l _c which is not less than the remaining bandwidth of bandwidth required to service s _i B _i;

Indicates that the link terminal k corresponds to the function fg required for the service s _i , and n _k indicates the k-th terminal of the link in the deployment solution l _c ;

Is a business delay,

It is the maximum tolerable delay of service S _i ;

In the link representing service s _i , any terminal does not form a loop; 0≤b _k ≤2 means that at most two services can be deployed on the terminal at the same time.

2. Solving configuration scheme

In response to the proposed objective function and constraints, this application has designed a resource allocation method to achieve stable operation of smart substations by optimizing costs and balancing equipment loads. The flow of resource configuration method is shown in Figure 1. The method is as follows.

Step 10: Initialize the use status of terminal equipment in the intelligent substation, and receive various business requests S.

Step 30: In accordance with the service reliability requirements, from high to low, select an alternative resource configuration scheme for each service according to the service range of each service in the multiple services, and form a set P of each service .

Step 40: Select an alternative resource configuration scheme with the smallest MOI value in the set P of each service according to the resource configuration model, and allocate resources according to the selected alternative resource configuration scheme.

Step 50. When the reliability of the alternative resource configuration scheme selected by Step 4 meets the service reliability requirements of each service, go to Step 80. The reliability of the alternative resource configuration scheme selected by Step 40 is not If the service reliability requirements of each service are met, go to Step 60.

Step 60: When there is an alternative resource configuration scheme other than the selected alternative resource configuration scheme in the set P corresponding to each service, update the set P corresponding to each service to the Alternative resource configuration scheme other than the selected alternative resource configuration scheme, and go to Step 40; there is no alternative resource configuration other than the selected alternative resource configuration scheme in the set P corresponding to each service In case of plan, go to Step 70.

Step 70: Recalculate the service scope of each business, reselect the alternative resource configuration scheme for each business according to the recalculated service scope of each business, and set the corresponding set P of each business Update to the newly selected backup resource allocation scheme and go to Step 40.

Step 80, end.

In an embodiment, the service range of the service can be calculated based on whether the delay between the start and end of the service exceeds the service tolerance experiment.

The following describes the implementation of this application in conjunction with simulation examples:

FIG. 2a is the service success rate of the three algorithms in the case where the service provided by the embodiment of the present application in the Poisson distribution arrives with a λ value equal to 1000; FIG. 2b shows the service provided in the embodiment of the present application in the Poisson distribution in the arrival state The business success rate of the three algorithms in the case where the value is equal to 1500; FIG. 2c is the business success rate of the three algorithms in the case that the service provided by the embodiment of the present application with the Poisson distribution reaching the lambda value equal to 2000; FIG. 2d is The service success rate of the three algorithms in the case that the service provided by the application example in the Poisson distribution arrival state is equal to 2500; FIG. 2e is the case where the service provided in the application example in the Poisson distribution arrival state is equal to 3,000 The business success rate of the following three algorithms; FIG. 2f is the business success rate of the three algorithms provided by the embodiments of the present application when the final steady state under different λ values. The three algorithms are: JP+picker, service chain mapping based on resource sharding (service function chain mapping with Resource Fragmentation Degree, SFCM-RFD) and the service based on cost, load balancing and reliability of this application method Chain mapping (service function chain with cost, load-balancing and reliability, SFCM-CBR), the success rate is the percentage of the number of service requests from the normal service to the departure to the total number. Figures 2a-2e show that at the initial stage, due to the occupation of terminal equipment resources, the success rate is gradually decreasing. After a period of time, it entered a stable state.

Figure 2f shows the business success rate of the three algorithms at different λ values when the final steady state is reached. When the arrival rate is higher, the terminal resource consumption also becomes larger. At this time, due to limited resources, the success rate of business completion will be reduced. By comparing the performance of multiple algorithms under the same λ value, it can be seen that the success rate of the algorithm of this application is significantly higher than that of the other two algorithms. And the larger the λ value, the more obvious this advantage. For example, when λ=1000, the algorithm of the present application improves the success rate by 6.7% and 33.3% respectively compared to the other two algorithms, and when λ=3000, it increases by 25% and 66.7%, respectively. The reason is that higher arrival rates require better load balancing adjustment capabilities and reliability assurance capabilities. This algorithm considers both of these. The results show that the proposed algorithm and the definition of equilibrium factors are effective.

Figure 3 shows how the terminal load balancing factor changes over time. In the first 250 time units, the load factor dropped sharply due to resource consumption. During this period, due to limited terminal resources, some business requests were rejected, so the success rate declined to some extent. After that, the terminal load state fluctuated slightly, and the success rate gradually converged to a stable value.

Figure 4 shows the cost of the terminal. It can be seen that the cost consumption of the algorithm of this application is greater than SFCM-RFD and better than JP+picker. But the reason is that SFCM-RFD only considers the resource availability of successful business request mapping, and does not consider the reliability index, so its cost consumption does not cover backup costs. This also led to the SFCM-RFD algorithm performing poorly on the business success rate indicator.

An embodiment of the present application further provides a substation. The substation includes a processor and a memory. The memory stores a computer program. When the computer program is executed by the processor, the processor implements any of the resource allocation methods described above.

An embodiment of the present application further provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, any one of the resource configuration methods described above is implemented.

Claims

A resource allocation method, including:

Initialize the use state of terminal equipment in the intelligent substation, and receive various service requests of the terminal equipment;

Calculate the service range of each service in the multiple services corresponding to the multiple service requests, and check the service reliability requirements of each service;

Selecting an alternative resource configuration scheme for each service according to the service range of each service in the multiple services according to the service reliability requirements from high to low, and forming a set P corresponding to each service;

Selecting an alternative resource configuration scheme with the smallest MOI value in the set P corresponding to each service according to the resource configuration model, and allocating resources according to the selected alternative resource configuration scheme;

When the reliability of the selected alternative resource configuration solution meets the service reliability requirements of each service, it ends;

When the reliability of the selected alternative resource configuration scheme does not meet the service reliability requirements of each service, determine whether the set P corresponding to each service has any of the selected alternative resource configuration schemes Alternative resource allocation plan;

When there is an alternative resource configuration solution other than the selected alternative resource configuration solution in the set P corresponding to each service, the set P corresponding to each service is updated to be in addition to the selection Alternative resource configuration scheme other than the alternative resource configuration scheme, and return to execute the alternative resource configuration scheme with the smallest MOI value in the set P corresponding to each service according to the resource configuration model, and according to the selected alternative The resource allocation scheme allocates resources; if there is no alternative resource allocation scheme other than the selected alternative resource allocation scheme in the set P corresponding to each business, the service of each business is recalculated Range, according to the recalculated service range of each service, reselect the backup resource configuration scheme for each service, update the set P corresponding to each service to the reselected backup resource configuration scheme, and return to the execution basis The resource configuration model selects the alternative resource configuration scheme with the smallest MOI value in the set P corresponding to each service, and allocates resources according to the selected alternative resource configuration scheme;

Among them, the resource configuration model is as follows:

Among them, MOI stands for importance metric,
Represents the cost of expenditure,
Represents the business balance, χ,
Are the weights of cost and business balance, respectively, s i represents the ith business,
P resi (k) for the remaining processing capacity of the terminal k, c resi (k) for the remaining storage capacity of the terminal k,; s i selected service costs resource allocation scheme l c, b is the service equalization factor
with
Respectively, the processing capacity and storage capacity consumed by the terminal k by the service si ;

For any embodiment showing the configuration of a link l c which is not less than the remaining bandwidth of bandwidth required to service s i B i;
Indicates that the functional sequence in the configuration scheme l c must be the same as the functional sequence required by the service S i ,
It means that the link terminal k has the function fg corresponding to the service s i ;
Is a business delay,
It is the maximum tolerable delay of service S i ;
In the link representing service s i , any terminal does not form a loop; b k represents the number of services that can be deployed on terminal k.
The method according to claim 1, wherein the expenditure cost includes terminal resource cost and path cost, terminal resource cost
for:

Among them, S i represents the i-th service, k represents the terminal label, n is the total number of terminals, and B i is the bandwidth required by the service S i .
The method according to claim 1, wherein

Where p resi(k) is the remaining processing capacity of terminal k, and c resi(k) is the remaining storage capacity of terminal k,
Is the remaining in-degree resources of terminal k, that is, the remaining access resources of terminal k
The remaining resources for terminal k,
Is the total bandwidth consumed by the service S i , β is the weight of the remaining capacity of the terminal, ω is the weight of the remaining resource of the terminal, and μ is the weight of the total bandwidth consumed by the service.
According to the method of claim 1, when the reliability of the selected alternative resource solution meets the service reliability requirements of each service, the method further comprises: calculating a terminal balance factor to measure the resource balance state after allocating resources, Wherein, the terminal balance factor represents the resource balance state in the operation state of the intelligent substation, and the terminal balance factor n b is:

Where p resi(k) is the remaining processing capacity of terminal k, and c resi(k) is the remaining storage capacity of terminal k,
Is the remaining in-degree resources of terminal k, that is, the remaining access resources of terminal k,
It is the terminal k's remaining out-of-degree resources, α is the weight of the terminal's remaining capacity, τ is the weight of the link's remaining bandwidth, and n is the number of terminals.
The method according to claim 1, wherein

Among them, S i represents the i-th service, k represents the terminal label, n is the total number of terminals,
Represents the processing delay of terminal k,
Represents the transmission delay from terminal h to terminal m,
Allocate the delay of the terminal k involved for the service S i resources.
A substation, comprising: a processor and a memory, the memory stores a computer program, and when the computer program is executed by the processor, the processor realizes the resource according to any one of claims 1-5 Configuration method.
A computer-readable storage medium storing a computer program, which when executed by a processor implements the resource configuration method according to any one of claims 1-5.