Automatic resource configuration method and system

Abstract

The invention discloses an automatic resource configuration method and system, and the method comprises the following steps: obtaining the initial data of a to-be-processed task from a user or a system, including a task type parameter and a resource limit parameter; generating a resource configuration combination set containing all possible resource configuration combinations according to the task type parameters and the resource limit parameters; for each resource configuration combination, a resource configuration scheme conforming to a constraint condition is obtained through calculation by using an algorithm, and it is ensured that resource allocation can meet task requirements to the maximum extent; the system has the advantages that the functions of task input, resource configuration, resource allocation, resource management, resource release, user interfaces and the like are integrated, and automation and intelligentization of resource management are achieved; an optimal resource allocation scheme is automatically calculated through an algorithm, so that the resource allocation efficiency is improved; the centralized management and control and flexible calling of the heterogeneous resources are realized, and the requirements of different tasks on the resources are met.

Description

Technical Field

[0001] The present invention belongs to the technical field of resource configuration, and in particular relates to a resource automatic configuration method and system. Background Art

[0002] With the deepening of "integration of industrialization and informationization", accompanied by the accelerated integration of new generation information technologies such as big data, cloud computing, and artificial intelligence with manufacturing technologies, the deepening of Internet applications, and the increasing strategic position of cyberspace, information security incidents in industrial control systems caused by insufficient protection measures have occurred frequently, and the security issues faced by industrial control systems have become increasingly complex. The importance of information security in industrial control systems has become increasingly prominent. Under the trend of integration of industrialization and informatization and intelligent manufacturing, the originally closed and isolated industrial control systems have gradually opened up industrial control networks with the Internet in order to meet the needs of system collaboration and information sharing. On the one hand, it has expanded the development space for industrial control, but on the other hand, it will inevitably face some traditional information security threats.

[0003] In order to implement the innovative development strategy of the Industrial Internet in depth, vigorously cultivate a team of high-quality network security technical and skilled personnel, accelerate the construction of the Industrial Internet security assurance system, support the construction of new network infrastructure, promote the construction of a strong manufacturing country and a strong network country, and promote the spirit of craftsmanship of continuous improvement, it is imperative to build a highly simulated training environment that conforms to the business processes of the Industrial Internet; especially in recent years, with the development of cyberspace target ranges and simulation technologies, combined with the business simulation system of the target range, the information network and business production network systems of various industries in the industrial system are highly simulated, providing researchers with technical drills, competitions, practical training, safety skills competitions and other full-business, full-process industrial control network security training support in a real business environment. Provide mature conditions.

[0004] The Industrial Internet simulation training platform is based on cloud computing, simulation virtualization technology, SDN technology, digital twin technology, and the combination of virtual and real technologies. Through virtual simulation of important equipment such as industrial equipment, industrial systems, security equipment, industrial networks, and the virtual-real interoperability of physical equipment, it realizes security training, attack and defense drills, competitive competitions, equipment evaluation, solution verification, and industrial control teaching.

[0005] A resource automatic configuration method and device with publication number CN110990156A, the patent discloses: obtaining initial data corresponding to the task to be processed, the initial data including: task type parameters and resource limit parameters corresponding to the task type parameters; obtaining a resource configuration combination set according to the task type parameters and the resource limit parameters, the resource configuration combination set including all resource configuration combinations for each task combination; for each resource configuration combination, respectively calculating a resource configuration scheme that meets the constraint conditions, and allocating resources for the corresponding task combination, so as to maximize the use of resources and thus improve resource utilization.

[0006] Traditional resource allocation methods have problems such as low resource utilization and slow configuration speed, and cannot meet the needs of the Industrial Internet simulation training platform for efficient and flexible resource management. Summary of the invention

[0007] The purpose of the present invention is to provide a method and system for automatically configuring resources to improve resource utilization and configuration efficiency.

[0008] To achieve the above object, the present invention provides the following technical solution: a resource automatic configuration method, comprising the following steps:

[0009] Obtaining initial data of the task to be processed from the user or the system, including task type parameters and resource limit parameters;

[0010] Generate a resource configuration combination set including all possible resource configuration combinations according to the task type parameter and the resource limit parameter;

[0011] For each resource configuration combination, use the algorithm to calculate the resource configuration plan that meets the constraints to ensure that resource allocation can maximize the task requirements;

[0012] Allocate resources according to the calculated resource allocation plan to ensure that the task combination can obtain the required resources;

[0013] Establish a range resource management platform to achieve real-time monitoring, dynamic scheduling and intelligent control of resources to ensure the effectiveness and efficiency of resource use;

[0014] After the task is completed, the distributed resource management algorithm and queue, as well as the multi-level cache storage mechanism that supports dynamic and static, can realize the rapid release of resources and improve the efficiency of resource reuse.

[0015] As a preferred technical solution of the present invention, the method for obtaining the initial data of the task to be processed from the user or the system is as follows:

[0016] For tasks submitted directly by users, users can enter initial data for the tasks through a graphical user interface, command line interface, or application program interface;

[0017] For tasks generated by the system, the system will automatically generate initial data for the task based on preset rules and strategies;

[0018] The data is verified to ensure its accuracy and completeness. Once verified, the data is formatted into a standard format that the system can handle and stored.

[0019] As a preferred technical solution of the present invention, the verification includes checking the data type and range.

[0020] As a preferred technical solution of the present invention, a method for generating a resource configuration combination set including all possible resource configuration combinations according to task type parameters and resource limit parameters is as follows:

[0021] Identify the types of resources available for configuration and the scope of availability of each resource;

[0022] According to the task type parameters and resource limit parameters, all possible resource configuration combinations are enumerated;

[0023] Filter out all legal resource configuration combinations.

[0024] As a preferred technical solution of the present invention, a method for calculating a resource configuration solution that meets the constraint conditions is as follows:

[0025] Identify the constraints that the resource allocation plan needs to meet;

[0026] Select an algorithm based on the constraints and characteristics of the problem;

[0027] Each resource configuration combination is used as the input of the algorithm, and the algorithm is executed to calculate the resource configuration solution that meets the constraints;

[0028] Evaluate the resource allocation plan output by the algorithm, and then select the best plan as the final resource allocation plan.

[0029] As a preferred technical solution of the present invention, the constraint conditions include that resource usage does not exceed the limit, task execution time meets the requirements, and resource utilization is maximized; the algorithm includes a greedy algorithm and a genetic algorithm.

[0030] As a preferred technical solution of the present invention, the method for realizing rapid release of resources includes the following:

[0031] When a task is completed, the system needs to be able to detect this event;

[0032] Once the task completion is detected, the system generates a resource recycling request;

[0033] Use distributed resource management algorithms to determine which resources can be released, and the order and method of release;

[0034] Put resource recycling requests into a queue and process them in order of priority;

[0035] When releasing resources, a multi-level cache storage mechanism is used to speed up the resource recovery process;

[0036] Execute resource release operations based on the results of distributed resource management algorithms and queue management.

[0037] As a preferred technical solution of the present invention, the shooting range resource management platform includes four major modules, namely: scene simulation, teaching training, competition drills, and system management.

[0038] The invention also discloses a resource automatic configuration system, comprising:

[0039] Task input module: used to receive the initial data of the task to be processed input by the user or the system, including task type parameters and resource limit parameters;

[0040] Resource configuration module: Generates a resource configuration combination set containing all possible resource configuration combinations based on the task information provided by the task input module, and uses an algorithm to calculate a resource configuration plan that meets the constraints;

[0041] Resource allocation module: allocates resources according to the resource allocation plan calculated by the resource allocation module to ensure that the task combination can obtain the required resources;

[0042] Resource management platform: realize real-time monitoring, dynamic scheduling and intelligent control of resources to ensure the effectiveness and efficiency of resource use;

[0043] Resource release module: After the task is completed, the distributed resource management algorithm and queue, as well as the multi-level cache storage mechanism that supports dynamic and static, are used to quickly release resources.

[0044] User interface module: provides a user-friendly interface to facilitate users to input task information, view resource allocation plans and resource usage.

[0045] Compared with the prior art, the present invention has the following beneficial effects:

[0046] Integrates the functions of task input, resource configuration, resource allocation, resource management, resource release and user interface, realizing the automation and intelligence of resource management;

[0047] The algorithm automatically calculates the optimal resource allocation plan, which improves the efficiency of resource allocation;

[0048] It realizes centralized control and flexible calling of heterogeneous resources, meeting the resource requirements of different tasks;

[0049] The unique distributed resource management algorithm and queue, as well as the multi-level cache storage mechanism, ensure the stability and reliability of resource allocation and release;

[0050] The present invention can be widely used in resource management in industrial Internet simulation training platforms, especially in the fields of teaching, research, drills, competitions and testing, and has broad application prospects and significant social and economic benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 This is a flow chart of the automatic resource configuration method of the present invention. DETAILED DESCRIPTION

[0052] 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.

[0053] Example 1

[0054] See also Figure 1 , is the first embodiment of the present invention, which provides a resource automatic configuration method, comprising the following steps:

[0055] Obtaining initial data of the task to be processed from the user or the system, including task type parameters and resource limit parameters;

[0056] Generate a resource configuration combination set including all possible resource configuration combinations according to the task type parameter and the resource limit parameter;

[0057] For each resource configuration combination, use the algorithm to calculate the resource configuration plan that meets the constraints to ensure that resource allocation can maximize the task requirements;

[0058] Allocate resources according to the calculated resource allocation plan to ensure that the task combination can obtain the required resources;

[0059] Establish a range resource management platform to achieve real-time monitoring, dynamic scheduling and intelligent control of resources to ensure the effectiveness and efficiency of resource use;

[0060] After the task is completed, the distributed resource management algorithm and queue, as well as the multi-level cache storage mechanism that supports dynamic and static, can realize the rapid release of resources and improve the efficiency of resource reuse.

[0061] In this embodiment, preferably, the method for obtaining the initial data of the task to be processed from the user or the system is as follows:

[0062] For tasks submitted directly by users, users can enter initial data of the tasks through a graphical user interface (GUI), a command line interface (CLI) or an application program interface (API); these data may include task type parameters (such as computationally intensive, data intensive, network communication type, etc.) and resource limit parameters (such as CPU usage limit, memory allocation, storage requirements, network bandwidth, etc.);

[0063] System task generation: For tasks generated by the system, such as scheduled tasks and system maintenance tasks, the system will automatically generate initial task data based on preset rules and policies; these data also include task type parameters and resource limit parameters, as well as additional information such as the time window for task execution and priority.

[0064] Data validation and formatting: Whether the data comes from users or systems, it needs to be validated to ensure the accuracy and completeness of the data, including checking the data type and range. After the validation, the data will be formatted into a standard format that the system can handle for subsequent processing.

[0065] Data storage and transmission: The validated and formatted data will be stored in the appropriate location (such as database, memory cache, etc.).

[0066] In this embodiment, preferably, the method for generating a resource configuration combination set including all possible resource configuration combinations according to the task type parameter and the resource limit parameter is as follows:

[0067] It is necessary to clearly define the types of resources that can be used for configuration (such as CPU, memory, storage, network, etc.) and the available range of each resource;

[0068] According to the task type parameters and resource limit parameters, all possible resource configuration combinations are enumerated; this can be achieved through loop, recursion or combination algorithms; for example, for the two resources of CPU and memory, their available ranges can be listed respectively, and then all possible CPU and memory combinations can be generated;

[0069] The generated resource combination set may contain some combinations that do not meet the constraints (e.g., resource usage exceeds the limit); therefore, it is necessary to screen out all legal resource configuration combinations, that is, those that meet the task type parameters and resource limit parameters;

[0070] The filtered resource configuration combination set will be stored in the appropriate location.

[0071] In this embodiment, preferably, the method for calculating the resource configuration solution that meets the constraint conditions is as follows:

[0072] Clarify the constraints that the resource allocation plan needs to meet, including that resource usage does not exceed the limit, task execution time meets requirements, and resource utilization is maximized;

[0073] Select appropriate algorithms, such as greedy algorithms and genetic algorithms, based on constraints and problem characteristics, and then design specific algorithm implementations, including algorithm steps, parameter settings, etc.;

[0074] Each resource configuration combination is used as the input of the algorithm, and the algorithm is executed to calculate the resource configuration scheme that meets the constraints; the output of the algorithm is one or more feasible resource configuration schemes;

[0075] Evaluate the resource allocation scheme output by the algorithm, usually based on indicators such as resource utilization, task execution efficiency, and cost; then select the best scheme as the final resource allocation scheme;

[0076] Store the selected resource configuration scheme in an appropriate location.

[0077] In this embodiment, preferably, the method for realizing rapid release of resources includes the following methods:

[0078] When a task is completed, the system needs to be able to detect this event through status monitoring, callback functions, event notifications, etc. during task execution;

[0079] Once the task is detected to be completed, the system will generate a resource recovery request; this request will contain detailed information about all resources occupied by the task;

[0080] Use a distributed resource management algorithm to determine which resources can be released, and the order and method of release; this algorithm needs to consider factors such as the sharing status of resources, the needs of other tasks, and the availability of resources;

[0081] Put resource recycling requests into a queue and process them in a certain priority order; this queue can ensure the orderliness and efficiency of resource recycling operations;

[0082] When releasing resources, a multi-level cache storage mechanism is used to speed up the resource recovery process, including storing the released resource information in a fast-access cache so that subsequent tasks can quickly obtain this information. At the same time, according to the dynamic and static characteristics of the resources, appropriate cache strategies can be selected to optimize the resource recovery efficiency.

[0083] According to the results of distributed resource management algorithms and queue management, execute resource release operations, including updating resource status, releasing physical resources (such as memory, storage, etc.), and updating the system's resource allocation table;

[0084] During the resource release process, the system status is continuously monitored to ensure the correctness and efficiency of resource release; at the same time, feedback information during the resource release process is collected to optimize subsequent resource management strategies.

[0085] In this embodiment, preferably, the shooting range resource management platform includes four major modules, namely: scene simulation, teaching training, competition drills, and system management;

[0086] Scenario simulation: The scenario simulation system has built-in multiple network security experiment scenarios. Users can use built-in scenarios or built-in simulation devices to dynamically build business scenarios on the visual networking page. This module is divided into two roles: scenario administrator and researcher. The scenario administrator is responsible for scenario management, task management, image management, component management, and user management operations. The researcher receives tasks issued by the scenario administrator and performs operations.

[0087] Teaching and training: Provide students with information security experimental learning on the platform; students can conduct relevant information security experiments here, integrating "learning, practice, testing, and evaluation"; this module is divided into two roles: tutor and student; tutor is responsible for student management, class management, learning plan, courseware management, examination evaluation, test paper management, and customized learning management for students; students receive course tasks, examination tasks and learning tasks issued by tutors for learning;

[0088] Competitive Drills: Provides theoretical competitions, CTF, red-blue competitions and other competition modes, supports individuals and teams to participate in competitive drills, and meets the requirements of "using competitions to replace practice, using competitions to replace training, using competitions to promote learning, and using competitions to promote construction"; this module is divided into five roles: organizer, participant, audience, director, and referee; organizer is responsible for the modification, creation, opening, closing, and topic management of theoretical competitions, CTF, and red-blue competitions, and participant user management; participants participate in the competitions associated with the organizer; audiences can watch the dynamics of participants displayed on the large screen of the competition; directors can control the ongoing competition; referees are responsible for judging and scoring the answers of participants;

[0089] System Management: Manages user allocation, virtual machines, logs, permissions and other operations of the entire system. This module only has the super administrator role; the super administrator is responsible for user management, virtual machine management, log management, permission management, system management, and system restore operations.

[0090] Example 2

[0091] See also Figure 1, which is a second embodiment of the present invention, and which provides a resource automatic configuration system, comprising

[0092] Task input module: used to receive the initial data of the task to be processed input by the user or the system, including task type parameters and resource limit parameters;

[0093] Resource configuration module: Generates a resource configuration combination set containing all possible resource configuration combinations based on the task information provided by the task input module, and uses an algorithm to calculate a resource configuration plan that meets the constraints;

[0094] Resource allocation module: allocates resources according to the resource allocation plan calculated by the resource allocation module to ensure that the task combination can obtain the required resources;

[0095] Resource management platform: realize real-time monitoring, dynamic scheduling and intelligent control of resources to ensure the effectiveness and efficiency of resource use;

[0096] Resource release module: After the task is completed, the distributed resource management algorithm and queue, as well as the multi-level cache storage mechanism that supports dynamic and static, are used to quickly release resources.

[0097] User interface module: provides a user-friendly interface to facilitate users to input task information, view resource allocation plans and resource usage.

[0098] Although the embodiments of the present invention have been shown and described, as detailed above, it will be understood by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A resource automatic configuration method, characterized in that: The steps include: Obtaining initial data of the task to be processed from the user or the system, including task type parameters and resource limit parameters; Generate a resource configuration combination set including all possible resource configuration combinations according to the task type parameter and the resource limit parameter; For each resource configuration combination, use the algorithm to calculate the resource configuration plan that meets the constraints to ensure that resource allocation can maximize the task requirements; Allocate resources according to the calculated resource allocation plan to ensure that the task combination can obtain the required resources; Establish a range resource management platform to achieve real-time monitoring, dynamic scheduling and intelligent control of resources to ensure the effectiveness and efficiency of resource use; After the task is completed, the distributed resource management algorithm and queue, as well as the multi-level cache storage mechanism that supports dynamic and static, can realize the rapid release of resources and improve the efficiency of resource reuse.

2. A resource automatic configuration method according to claim 1, characterized in that: The implementation method of obtaining the initial data of the task to be processed from the user or the system is as follows: For tasks submitted directly by users, users can be allowed to input initial data for the task through a graphical user interface, command line interface, or application program interface; For tasks generated by the system, the system will automatically generate initial data for the task based on preset rules and strategies; The data is verified to ensure its accuracy and completeness. Once verified, the data is formatted into a standard format that the system can handle and stored.

3. A resource automatic configuration method according to claim 2, characterized in that: The verification includes checking the data type and range.

4. The method for automatic resource configuration according to claim 1, characterized in that: The method for generating a resource configuration combination set containing all possible resource configuration combinations according to the task type parameters and resource limit parameters is as follows: Identify the types of resources available for configuration and the scope of availability of each resource; According to the task type parameters and resource limit parameters, all possible resource configuration combinations are enumerated; Filter out all legal resource configuration combinations.

5. The method for automatic resource configuration according to claim 1, characterized in that: The method for calculating the resource allocation solution that meets the constraints is as follows: Identify the constraints that the resource allocation plan needs to meet; Select an algorithm based on the constraints and characteristics of the problem; Each resource configuration combination is used as the input of the algorithm, and the algorithm is executed to calculate the resource configuration solution that meets the constraints; Evaluate the resource allocation plan output by the algorithm, and then select the best plan as the final resource allocation plan.

6. A method for automatic resource configuration according to claim 5, characterized in that: The constraints include that resource usage does not exceed the limit, task execution time meets the requirements, and resource utilization is maximized; the algorithms include greedy algorithms and genetic algorithms.

7. The method for automatic resource configuration according to claim 1, characterized in that: The following methods are used to quickly release resources: When a task is completed, the system needs to be able to detect this event; Once the task completion is detected, the system generates a resource recycling request; Use distributed resource management algorithms to determine which resources can be released, and the order and method of release; Put resource recycling requests into a queue and process them in order of priority; When releasing resources, a multi-level cache storage mechanism is used to speed up the resource recovery process; Execute resource release operations based on the results of distributed resource management algorithms and queue management.

8. The method for automatic resource configuration according to claim 1, characterized in that: The shooting range resource management platform includes four major modules: scene simulation, teaching training, competition drills, and system management.

9. A resource automatic configuration system, characterized in that: include Task input module: used to receive the initial data of the task to be processed input by the user or the system, including task type parameters and resource limit parameters; Resource configuration module: Generates a resource configuration combination set containing all possible resource configuration combinations based on the task information provided by the task input module, and uses an algorithm to calculate a resource configuration plan that meets the constraints; Resource allocation module: allocates resources according to the resource allocation plan calculated by the resource allocation module to ensure that the task combination can obtain the required resources; Resource management platform: realize real-time monitoring, dynamic scheduling and intelligent control of resources to ensure the effectiveness and efficiency of resource use; Resource release module: After the task is completed, the distributed resource management algorithm and queue, as well as the multi-level cache storage mechanism that supports dynamic and static, are used to quickly release resources. User interface module: provides a user-friendly interface to facilitate users to input task information, view resource allocation plans and resource usage.

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