Resource scheduling method and device for important science and technology infrastructure and medium

Abstract

According to the resource scheduling method and device for the important science and technology infrastructure and the medium, scene elements are extracted according to the characteristics of the important science and technology infrastructure, and a collaborative environment is abstracted; constructing an E-CARGO model according to the obtained scene elements and the collaborative environment, and defining model parameters; calculating the use efficiency of different resource entities according to the E-CARGO model, and determining a scheme range meeting a preset efficiency requirement; according to the scheme range and the use efficiency of different resource entities, determining an objective function meeting the maximization of the overall efficiency of resources and corresponding constraint conditions; and solving according to the objective function and the constraint condition to obtain an optimal scheduling scheme. According to the scheme, an efficient resource allocation strategy is provided, and the resource utilization efficiency is optimized.

Description

Technical Field

[0001] The present invention relates to the field of resource management technology, and in particular to a resource scheduling method, device and medium for major scientific and technological infrastructure. Background Art

[0002] The opening and sharing of major scientific and technological infrastructure plays an important role in open science. It is of great significance to promote the development of science and technology, improve the resource utilization efficiency of major facilities and promote the output of scientific results. Due to limited resources, the allocation strategy of major facilities needs to be flexibly adjusted according to different resource conditions.

[0003] However, due to the scarcity of resources in major scientific and technological infrastructure, major scientific and technological infrastructure services cannot meet the needs of all researchers or teams at the same time. Therefore, major scientific and technological infrastructure urgently needs to propose efficient resource allocation strategies from the aspects of open sharing, utilization efficiency, and service diversification to optimize resource utilization efficiency. Summary of the invention

[0004] To solve the above technical problems, the present invention provides a resource scheduling method, device and medium for major scientific and technological infrastructure, which can provide an efficient resource allocation strategy and optimize resource utilization efficiency.

[0005] An embodiment of the present invention provides a method for resource scheduling of a major scientific and technological infrastructure, the method comprising: Extract scene elements based on the characteristics of major scientific and technological infrastructure and abstract the collaborative environment; Construct the E-CARGO model based on the obtained scenario elements and collaborative environment, and define the model parameters; Calculate the utilization efficiency of different resource entities according to the E-CARGO model and determine the scope of the solution that meets the preset efficiency requirements; According to the scope of the scheme and the utilization efficiency of different resource entities, determine the objective function and corresponding constraints that maximize the overall efficiency of resources; The objective function and the constraint conditions are solved to obtain the optimal scheduling solution.

[0006] Preferably, scene elements are extracted based on the characteristics of major scientific and technological infrastructure, and the collaborative environment is abstracted, including: Abstract different resource types of major scientific and technological infrastructure into different resource entities and define the corresponding resource states; Determine the users of different resource entities as user entities; Abstract different scientific research activities into different types of resource tasks, and define the resource actions generated by different tasks on different resource entities; Connect different resource entities with user entities to build a collaborative network; Tasks are operated through different collaboration rules and protocols, and different resource actions are executed in the collaborative network to form a collaborative environment.

[0007] Furthermore, the resource entities include computing resources, storage resources, instrument resources and atomic resources; The resource status includes the availability, usage status and configuration information of the resource; The resource tasks include data collection, data analysis, and model training; The resource actions include resource application, resource allocation, resource use and resource release.

[0008] Preferably, the E-CARGO model ； The model parameters defined are: Role Requirements Vector , represents the number of users or projects that the j-th resource entity can satisfy at the same time; Time Matrix , represents the estimated completion time assigned to the i-th agent by the j-th resource entity; Priority Matrix , represents the priority of the i-th agent to the j-th resource entity; Dynamic Assessment Matrix , represents the efficiency performance of the i-th agent when using the j-th resource entity; in, C represents a set of classes, and O represents a set of objects; A represents a set of agents, i.e., collaborating individuals; M Represents a group of messages. R Represents a set of roles, i.e., resource tasks, E represents an abstract collaborative environment; G Represents a group set; s 0 represents the initial state of the model; H represents a group of users.

[0009] Preferably, the utilization efficiency of different resource entities is calculated according to the E-CARGO model, and the scope of the solution that meets the preset efficiency requirements is determined, including: Constructing an efficiency scoring matrix based on resource priorities, time selection, and agent-selected resources; According to the efficiency scoring matrix, the utilization efficiency of each resource entity in each scheme allocated to each resource applicant is determined, thereby determining the overall utilization rate of different schemes; Solutions with overall utilization rates greater than the efficiency requirement are included in the solution range.

[0010] Furthermore, the efficiency scoring matrix ; in, represents the utilization efficiency of the i-th agent on the j-th resource entity, is the priority matrix, which indicates the priority of the i-th agent to the j-th resource entity. is a dynamic evaluation matrix, which represents the efficiency performance of the i-th agent when using the j-th resource entity. is a time matrix, which represents the estimated completion time of the j-th resource entity assigned to the i-th agent.

[0011] Preferably, the objective function includes ; The constraints include: ; ; ; ; in, represents resource utilization, m represents the number of agents, n represents the number of resource entities, represents the scheme of assigning the j-th resource entity to the i-th agent, represents the utilization efficiency of the i-th agent on the j-th resource entity, represents the role requirement vector of the j-th resource entity, is a time matrix, which represents the estimated completion time of the j-th resource entity assigned to the i-th agent. represents the maximum available time of the ith agent.

[0012] The embodiment of the present invention further provides a resource scheduling device for major scientific and technological infrastructure, the device comprising: The abstraction module is used to extract scene elements based on the characteristics of major scientific and technological infrastructure and abstract the collaborative environment; Definition module, used to build E-CARGO model according to the obtained scene elements and collaborative environment, and define model parameters; An efficiency module, used to calculate the utilization efficiency of different resource entities according to the E-CARGO model, and determine the scope of solutions that meet the preset efficiency requirements; The objective module is used to determine the objective function and corresponding constraints that satisfy the maximization of the overall resource efficiency according to the scope of the solution and the utilization efficiency of different resource entities; The solution module is used to solve the objective function and the constraint conditions to obtain the optimal scheduling solution.

[0013] An embodiment of the present invention also provides a computer-readable storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute the resource scheduling method for major scientific and technological infrastructure as described in any one of the above embodiments.

[0014] An embodiment of the present invention also provides a resource scheduling device for major scientific and technological infrastructure, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and when the processor executes the computer program, it implements the resource scheduling method for major scientific and technological infrastructure as described in any one of the above embodiments.

[0015] The resource scheduling method, device and medium of the major scientific and technological infrastructure provided by the present invention extract scene elements according to the characteristics of the major scientific and technological infrastructure, and abstract the collaborative environment; construct an E-CARGO model according to the obtained scene elements and collaborative environment, and define model parameters; calculate the utilization efficiency of different resource entities according to the E-CARGO model, and determine the scope of the scheme that meets the preset efficiency requirements; determine the objective function and corresponding constraints that meet the maximization of the overall resource efficiency according to the scope of the scheme and the utilization efficiency of different resource entities; solve according to the objective function and the constraints to obtain the optimal scheduling scheme. The present application scheme optimizes resource utilization efficiency by providing an efficient resource allocation strategy. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a flowchart of a resource scheduling method for a major scientific and technological infrastructure provided by an embodiment of the present invention; Figure 2 It is a structural schematic diagram of a resource scheduling device for a major scientific and technological infrastructure provided by an embodiment of the present invention; Figure 3 It is a structural diagram of a resource scheduling device for a major scientific and technological infrastructure provided by another embodiment of the present invention. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] The present invention provides a method for resource scheduling of a major scientific and technological infrastructure. Figure 1, is a flow chart of a resource scheduling method for a major scientific and technological infrastructure provided by an embodiment of the present invention, wherein steps S1 to S3 of the method are as follows: Step S1, extracting scene elements according to the characteristics of major scientific and technological infrastructure and abstracting the collaborative environment; Step S2, constructing an E-CARGO model according to the obtained scene elements and collaborative environment, and defining model parameters; Step S3, calculating the utilization efficiency of different resource entities according to the E-CARGO model, and determining the scope of the solution that meets the preset efficiency requirements; Step S4, determining an objective function and corresponding constraints that satisfy the maximization of overall resource efficiency according to the scope of the solution and the utilization efficiency of different resource entities; Step S5, solving according to the objective function and the constraint conditions to obtain the optimal scheduling solution.

[0019] In the specific implementation of this embodiment, the research on major scientific and technological infrastructure is mainly focused on exploring its output benefits, evaluation mechanisms, infrastructure relevance, etc., and less attention is paid to how to improve allocation efficiency by optimizing resource allocation.

[0020] Resource allocation for major scientific and technological infrastructure is a complex issue involving efficiency, scientificity, and scalability. To achieve efficient resource allocation, it is necessary to use methods such as entity recognition, resource abstraction, and task abstraction to extract scene elements from the scene features of major infrastructure and abstract the collaborative environment; The E-CARGO model is further used to make decisions and schedule the allocation of major infrastructure resources. That is, the E-CARGO model is constructed according to the obtained scenario elements and collaborative environment, formalized for modeling, and the model parameters are defined.

[0021] E-CARGO can highly abstract collaborative systems. In collaborative systems, roles can be used to describe the relationships in the collaborative process, but it is still difficult to achieve system collaboration using only roles. Therefore, in order to achieve better collaboration between members in the system, we need to use the E-CARGO model to model the collaborative process. Generally speaking, the E-CARGO model can clearly define the collaborative process. As the role player, the agent processes the messages sent by the role, accesses the object with the authority specified by its role, and participates in the collaborative process. The role is a message exchanger and scheduler. The environment is specified by roles and objects. The group is composed of dynamic agents in the environment who play roles. A method for allocation, sharing and assignment of major scientific and technological infrastructure based on the E-CARGO model. This method can process a large amount of data in a short time, quickly solve the optimal allocation plan, and significantly improve the efficiency of resource allocation, thereby providing managers with efficient and reliable decision support.

[0022] The utilization efficiency of different resource entities is calculated according to the E-CARGO model, and the scope of the scheme that meets the preset efficiency requirements is determined; the scheme T that meets the resource utilization efficiency is executable. Otherwise, the allocation fails.

[0023] This article indicates whether a resource is assigned to a resource applicant.

[0024] The overall utilization efficiency value σ of major scientific and technological infrastructure indicates the overall resource utilization efficiency of all users or teams assigned to resources. The larger the value of σ, the higher the overall utilization efficiency.

[0025] According to the scope of the scheme and the utilization efficiency of different resource entities, determine the objective function and corresponding constraints that maximize the overall efficiency of resources; The objective function and the constraint conditions are solved to obtain the optimal scheduling solution.

[0026] This application uses the E-CARGO model to model and formalize the resource allocation problem, which can quickly solve the optimal allocation solution and significantly improve the efficiency of resource allocation. Compared with traditional methods, the present invention can process a large amount of data in a short time and achieve a solution in seconds, greatly improving the efficiency of resource allocation.

[0027] In another embodiment provided by the present invention, the step S2 specifically includes the following steps: Abstract different resource types of major scientific and technological infrastructure into different resource entities and define the corresponding resource states; Determine the users of different resource entities as user entities; Abstract different scientific research activities into different types of resource tasks, and define the resource actions generated by different tasks on different resource entities; Connect different resource entities with user entities to build a collaborative network; Tasks are operated through different collaboration rules and protocols, and different resource actions are executed in the collaborative network to form a collaborative environment.

[0028] In the specific implementation of this embodiment, methods such as entity recognition, resource abstraction, and task abstraction are used to abstract the collaborative environment of this complex problem of major infrastructure clusters; When performing entity recognition, due to the professionalism and domain-specificity of major scientific and technological infrastructure, different major scientific and technological infrastructure have different resources C, which usually cover multiple fields such as physics, chemistry, and materials science, and are reflected in laboratory equipment, data centers, computing resources, radiation light sources, etc.

[0029] According to different resource types: major scientific and technological infrastructure entities are further abstracted into different resource entities for expression, and the resource status of each type of entity resource needs to be defined.

[0030] The users of different resource entities are identified as user entities, which are scientific research teams, researchers, projects, etc. that use these resources.

[0031] Scientific research activities are abstracted into a series of tasks R. When users carry out tasks, they need the support of resources, so they change the resources and define the resource actions generated by different tasks on different resource entities, thereby associating resources and tasks.

[0032] Then, an abstract collaborative environment is created to connect different major scientific and technological infrastructure resources with user entities to form a collaborative network. Tasks are performed through different collaborative regulations and protocols, and resource actions such as applying for, allocating, using and releasing resources are performed in the network, thus forming a collaborative environment.

[0033] In this collaborative environment, the core of resource allocation decision-making is to improve allocation efficiency, which mainly includes resource selection, priority sorting and timetable arrangement. When allocating resources, efficient resource scheduling is required, and rapid resource allocation is achieved by designing an optimized scheduling algorithm. The design of the scheduling algorithm considers the following key factors: resource utilization, task priority, scientific research needs and optimal arrangement of the schedule. Through these measures, the efficiency and scientificity of resource allocation are ensured, while meeting the needs of different tasks and users. In the actual allocation of major scientific and technological infrastructure resources, managers need to reasonably allocate the use time of the infrastructure according to the scientific research capabilities and needs of different regions, and allocate resource quotas to scientific research teams in different disciplines to meet diverse scientific research needs. The resource allocation method for major scientific and technological infrastructure based on the E-CARGO model is a solution to achieve efficient resource allocation by optimizing resource allocation decisions and task scheduling in this collaborative environment.

[0034] In another embodiment provided by the present invention, the resource entity includes computing resources, storage resources, instrument resources and atomic resources; The resource status includes the availability, usage status and configuration information of the resource; The resource tasks include data collection, data analysis, and model training; The resource actions include resource application, resource allocation, resource use and resource release.

[0035] Specifically, when abstracting resource entities, major scientific and technological infrastructure entities are further abstracted into different resource types for expression, such as computing resources, storage resources, instrument resources, atomic resources, etc. At the same time, the resource status of each type of entity resource needs to be defined, including resource availability, usage status and configuration information, to support efficient allocation decisions.

[0036] Scientific research activities are abstracted into a series of tasks R, such as data collection, data analysis, model training, etc. These tasks will serve as the basic units for user resource application. When users carry out tasks, they need the support of resources, so they generate a series of actions A on the resources, thereby associating resources with tasks, including resource application, allocation, use and release.

[0037] Through the abstraction of scenarios and environments, flexible modeling can be performed according to different needs to adapt to a variety of scenarios and constraints. For example, each agent can only apply for one resource role, and each resource role can serve multiple agents. This flexible allocation strategy can meet diverse scientific research needs.

[0038] In another embodiment provided by the present invention, the E-CARGO model ； The model parameters defined are: Role Requirements Vector , represents the number of users or projects that the j-th resource entity can satisfy at the same time; Time Matrix , represents the estimated completion time assigned to the i-th agent by the j-th resource entity; Priority Matrix , represents the priority of the i-th agent to the j-th resource entity; Dynamic Assessment Matrix , represents the efficiency performance of the i-th agent when using the j-th resource entity; in, C represents a set of classes, and O represents a set of objects; A represents a set of agents, i.e., collaborating individuals; M Represents a group of messages. R Represents a set of roles, i.e., resource tasks, E represents an abstract collaborative environment; G Represents a group set; s 0 represents the initial state of the model; H represents a group of users.

[0039] In the specific implementation of this embodiment, the E-CARGO model is defined as: .

[0040] Represents the model, which abstractly describes the components of a collaborative system.

[0041] Among them, C is a set of classes; O is a set of objects; A (Agent) is a set of agents (collaborative individuals); M represents a set of messages; R (Role) represents a set of roles (i.e., the abstraction of tasks); E is used for abstract collaborative environments; G (Group) represents a group set; s 0 is the initial state of the system; H is a set of users.

[0042] Define m as the cardinality of the agent set, which expresses the number of agents in set A (m = |A|), and n as the cardinality of the role set, which expresses the number of roles in set R (n = |R|). i represents an agent, and j represents a resource entity, i.e., a role.

[0043] Define the role set R, the role set vector is an m-dimensional vector, and the role individual is defined as r =<id, ®> , where id is the role identifier and ® is the set of role attribute requirements. The set of roles is extracted for each major scientific and technological infrastructure.

[0044] Define the agent set A, the agent set vector is an n-dimensional vector, and the agent individual is a =<id,> , where id is the agent's identifier, is a collection of agents, and corresponds to the attributes required in the group. Each user or project that applies for scientific and technological infrastructure resources is a collection of agents. Each agent can apply for a role, and a role can serve multiple agents.

[0045] Define the role requirement vector L, which represents the lower limit of the role range of group g in environment e. represents the number of users or projects that can be satisfied by each major scientific and technological infrastructure at the same time, .

[0046] Time Matrix is a Matrix, where It represents the estimated completion time when the j-th resource role is assigned to the i-th agent.

[0047] The priority matrix P is a Matrix, where Indicates the priority of the i-th agent for the j-th resource.

[0048] The dynamic evaluation matrix U of major scientific and technological infrastructure efficiency is a Matrix, where It represents the efficiency performance of the i-th agent when using the j-th resource.

[0049] By introducing a dynamic efficiency evaluation matrix, we can monitor the resource utilization efficiency of agents in real time and dynamically adjust resource allocation strategies based on the latest efficiency performance. This dynamic evaluation mechanism ensures the scientific nature and flexibility of resource allocation and can be optimized based on actual usage.

[0050] In another embodiment provided by the present invention, the step S3 specifically includes: Construct a comprehensive efficiency scoring matrix based on resource priorities, time selection, and agent-selected resources; According to the comprehensive efficiency scoring matrix, the utilization efficiency of each resource entity in each scheme allocated to each resource applicant is determined, thereby determining the overall utilization rate of different schemes; Solutions with overall utilization rates greater than the efficiency requirement are included in the solution range.

[0051] In the specific implementation of this embodiment, the efficiency scoring matrix takes into account factors such as resource priority, time selection, and agent-selected resources to construct the efficiency scoring matrix.

[0052] The scoring result of the efficiency scoring matrix reflects the overall utilization of resource j by agent i. The value range of the overall utilization performance value is 0 to 1, where 1 represents the highest utilization efficiency and 0 represents the lowest utilization efficiency.

[0053] By determining the utilization efficiency of each resource entity allocated to each resource applicant in each scheme, the utilization efficiency of each resource entity scheduling in the comprehensive scheme is determined to determine the overall utilization rate of different schemes; For a certain resource utilization efficiency plan T, T is also an m×n matrix. , indicating whether role j is assigned to agent i. If every role j is executable, that is, , then the solution that satisfies resource utilization efficiency is executable. Otherwise, the allocation fails.

[0054] The solutions whose overall utilization rate is greater than the efficiency requirement are included in the solution range to obtain a solution range that meets the resource requirements.

[0055] In another embodiment provided by the present invention, the efficiency scoring matrix ; in, represents the utilization efficiency of the i-th agent on the j-th resource entity, is the priority matrix, which indicates the priority of the i-th agent to the j-th resource entity. is a dynamic evaluation matrix, which represents the efficiency performance of the i-th agent when using the j-th resource entity. is a time matrix, which represents the estimated completion time of the j-th resource entity assigned to the i-th agent.

[0056] Specifically, the efficiency scoring matrix considers factors such as resource priority, time selection, and agent-selected resources. Q is a Matrix, representing Responsible Efficiency Rating Matrix It means that each user or project applying for major scientific and technological infrastructure resources has a corresponding efficiency score, which comprehensively considers resource priority, time selection, and agent's efficiency in using resources, and reflects the overall utilization rate of agent i for resource j. The value range of the overall utilization rate performance value is 0 to 1, where 1 represents the highest utilization efficiency and 0 represents the lowest utilization efficiency. Specifically, the comprehensive efficiency score The calculation formula is: .

[0057] In another embodiment provided by the present invention, the objective function includes ; The constraints include: ; ; ; ; in, represents resource utilization, m represents the number of agents, n represents the number of resource entities, represents the scheme of assigning the j-th resource entity to the i-th agent, represents the utilization efficiency of the i-th agent on the j-th resource entity, represents the role requirement vector of the j-th resource entity, is a time matrix, which represents the estimated completion time of the j-th resource entity assigned to the i-th agent. It represents the maximum available time of the ith agent, and allocates the time required to fulfill the task to ensure that the task is completed on time.

[0058] This application scheme constructs a comprehensive efficiency scoring matrix by comprehensively considering factors such as resource priority, time selection, and agent resource utilization efficiency. This method transforms complex resource allocation problems into single-objective optimization problems, avoids the complexity of multi-objective solutions, and significantly improves the efficiency of resource allocation. By constructing an efficiency scoring matrix, the resource allocation efficiency is directly optimized, the solution process is simplified, and the solution speed is improved. The introduction of an efficiency dynamic evaluation matrix can monitor the agent's resource utilization efficiency in real time and dynamically adjust the resource allocation strategy based on the latest efficiency performance. This dynamic evaluation mechanism ensures the scientificity and flexibility of resource allocation.

[0059] In another embodiment provided by the present invention, see Figure 2 , is a schematic diagram of a structure of a resource scheduling device for a major scientific and technological infrastructure provided by an embodiment of the present invention, the device comprising: The abstraction module is used to extract scene elements based on the characteristics of major scientific and technological infrastructure and abstract the collaborative environment; Definition module, used to build E-CARGO model according to the obtained scene elements and collaborative environment, and define model parameters; An efficiency module, used to calculate the utilization efficiency of different resource entities according to the E-CARGO model, and determine the scope of solutions that meet the preset efficiency requirements; The objective module is used to determine the objective function and corresponding constraints that satisfy the maximization of the overall resource efficiency according to the scope of the solution and the utilization efficiency of different resource entities; The solution module is used to solve the objective function and the constraint conditions to obtain the optimal scheduling solution.

[0060] It should be noted that the resource scheduling device for major scientific and technological infrastructure provided in the embodiment of the present invention can execute the resource scheduling method for major scientific and technological infrastructure described in any of the above embodiments, and the specific functions of the resource scheduling device for major scientific and technological infrastructure will not be repeated here.

[0061] See also Figure 3 , is a schematic diagram of the structure of a resource scheduling device for a major scientific and technological infrastructure provided by another embodiment of the present invention. The resource scheduling device for a major scientific and technological infrastructure of this embodiment includes: a processor, a memory, and a computer program stored in the memory and executable on the processor, such as a resource scheduling program for a major scientific and technological infrastructure. When the processor executes the computer program, the steps of the resource scheduling method for each major scientific and technological infrastructure described above are implemented, such as Figure 1 Alternatively, the processor implements the functions of each module in the above-mentioned device embodiments when executing the computer program.

[0062] Exemplarily, the computer program may be divided into one or more modules / units, and the one or more modules / units are stored in the memory and executed by the processor to complete the present invention. The one or more modules / units may be a series of computer program instruction segments capable of completing specific functions, and the instruction segments are used to describe the execution process of the computer program in the resource scheduling device of the major scientific and technological infrastructure. For example, the computer program may be divided into modules, and the specific functions of each module are not described again.

[0063] The resource scheduling device of the major scientific and technological infrastructure may be a computing device such as a desktop computer, a notebook, a PDA, and a cloud server. The resource scheduling device of the major scientific and technological infrastructure may include, but is not limited to, a processor and a memory. Those skilled in the art may understand that the schematic diagram is only an example of a resource scheduling device of a major scientific and technological infrastructure, and does not constitute a limitation on the resource scheduling device of the major scientific and technological infrastructure. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the resource scheduling device of the major scientific and technological infrastructure may also include input and output devices, network access devices, buses, etc.

[0064] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the resource scheduling device of the major scientific and technological infrastructure, and uses various interfaces and lines to connect various parts of the resource scheduling device of the entire major scientific and technological infrastructure.

[0065] The memory can be used to store the computer program and / or module, and the processor realizes various functions of the resource scheduling device of the major scientific and technological infrastructure by running or executing the computer program and / or module stored in the memory, and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area can store data created according to the use of the mobile phone (such as audio data, phone book, etc.), etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0066] Wherein, if the module / unit integrated in the resource scheduling device of the major scientific and technological infrastructure is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Wherein, the computer program includes computer program code, and the computer program code can be in code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium, etc.

[0067] It should be noted that the device embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. In addition, in the accompanying drawings of the device embodiments provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, which may be specifically implemented as one or more communication buses or signal lines. A person of ordinary skill in the art may understand and implement it without paying any creative effort.

[0068] The above is a preferred embodiment of the present invention. It should be pointed out that a person skilled in the art can make several improvements and modifications without departing from the principle of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A resource scheduling method for major scientific and technological infrastructure, characterized in that: The method comprises: Extract scene elements based on the characteristics of major scientific and technological infrastructure and abstract the collaborative environment; Construct the E-CARGO model based on the obtained scenario elements and collaborative environment, and define the model parameters; Calculate the utilization efficiency of different resource entities according to the E-CARGO model and determine the scope of the solution that meets the preset efficiency requirements; According to the scope of the scheme and the utilization efficiency of different resource entities, determine the objective function and corresponding constraints that maximize the overall efficiency of resources; The objective function and the constraint conditions are solved to obtain the optimal scheduling solution.

2. The resource scheduling method for major scientific and technological infrastructure according to claim 1, characterized in that: Extract scene elements based on the characteristics of major scientific and technological infrastructure and abstract the collaborative environment, including: Abstract different resource types of major scientific and technological infrastructure into different resource entities and define the corresponding resource states; Determine the users of different resource entities as user entities; Abstract different scientific research activities into different types of resource tasks, and define the resource actions generated by different tasks on different resource entities; Connect different resource entities with user entities to build a collaborative network; Tasks are operated through different collaboration rules and protocols, and different resource actions are executed in the collaborative network to form a collaborative environment.

3. The resource scheduling method for major scientific and technological infrastructure according to claim 2, characterized in that: The resource entities include computing resources, storage resources, instrument resources and atomic resources; The resource status includes the availability, usage status and configuration information of the resource; The resource tasks include data collection, data analysis, and model training; The resource actions include resource application, resource allocation, resource use and resource release.

4. The resource scheduling method for major scientific and technological infrastructure according to claim 1, characterized in that: The E-CARGO Model ; The model parameters defined are: Role Requirements Vector , represents the number of users or projects that the j-th resource entity can satisfy at the same time; Time Matrix , represents the estimated completion time assigned to the i-th agent by the j-th resource entity; Priority Matrix , represents the priority of the i-th agent to the j-th resource entity; Dynamic Assessment Matrix , represents the efficiency performance of the i-th agent when using the j-th resource entity; in, C represents a set of classes, and O represents a set of objects; A represents a set of agents, i.e., collaborating individuals; M Represents a group of messages. R Represents a set of roles, i.e., resource tasks, E represents an abstract collaborative environment; G Represents a group set; s 0 represents the initial state of the model; H represents a group of users.

5. The resource scheduling method for major scientific and technological infrastructure according to claim 1, characterized in that: The utilization efficiency of different resource entities is calculated according to the E-CARGO model, and the scope of the solution that meets the preset efficiency requirements is determined, including: Constructing an efficiency scoring matrix based on resource priorities, time selection, and agent-selected resources; According to the efficiency scoring matrix, the utilization efficiency of each resource entity in each scheme allocated to each resource applicant is determined, thereby determining the overall utilization rate of different schemes; Solutions with overall utilization rates greater than the efficiency requirement are included in the solution range.

6. The resource scheduling method for major scientific and technological infrastructure according to claim 5, characterized in that: The efficiency scoring matrix ; in, represents the utilization efficiency of the i-th agent on the j-th resource entity, is the priority matrix, which indicates the priority of the i-th agent to the j-th resource entity. is a dynamic evaluation matrix, which represents the efficiency performance of the i-th agent when using the j-th resource entity. is a time matrix, which represents the estimated completion time of the j-th resource entity assigned to the i-th agent.

7. The resource scheduling method for major scientific and technological infrastructure according to claim 1, characterized in that: The objective function includes ; The constraints include: ; ； ； ； in, represents resource utilization, m represents the number of agents, n represents the number of resource entities, represents the scheme of assigning the j-th resource entity to the i-th agent, represents the utilization efficiency of the i-th agent on the j-th resource entity, represents the role requirement vector of the j-th resource entity, is a time matrix, which represents the estimated completion time of the j-th resource entity assigned to the i-th agent. represents the maximum available time of the ith agent.

8. A resource scheduling device for major scientific and technological infrastructure, characterized in that: The device comprises: The abstraction module is used to extract scene elements based on the characteristics of major scientific and technological infrastructure and abstract the collaborative environment; Definition module, used to build E-CARGO model according to the obtained scene elements and collaborative environment, and define model parameters; An efficiency module, used to calculate the utilization efficiency of different resource entities according to the E-CARGO model, and determine the scope of solutions that meet the preset efficiency requirements; The objective module is used to determine the objective function and corresponding constraints that satisfy the maximization of the overall resource efficiency according to the scope of the solution and the utilization efficiency of different resource entities; The solution module is used to solve the objective function and the constraint conditions to obtain the optimal scheduling solution.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute the resource scheduling method for major scientific and technological infrastructure as described in any one of claims 1 to 7.

10. A resource scheduling device for major scientific and technological infrastructure, characterized in that: The method comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, the method for resource scheduling of major scientific and technological infrastructure as described in any one of claims 1 to 7 is implemented.

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