Multi-platform distributed cloud organization integrated simulation system and method

Abstract

The invention discloses a multi-platform distributed cloud organization integrated simulation system and method, and the system comprises an operation process subsystem and a decision subsystem, and the operation process subsystem carries out the simulation of cloud nodes, node dynamic cloud entering, resource pooling, resource pool scheduling, scale dynamic telescoping, and human-computer interaction processes in the typical application process of a multi-platform distributed cloud organization; and the decision-making subsystem carries out a decision-making process. According to the multi-platform distributed cloud organization concept and scene design and DoDAF-based multi-platform distributed cloud organization system architecture design, a multi-platform distributed cloud organization integrated simulation system is built, and a multi-platform distributed cloud organization operation process and a multi-platform distributed cloud organization decision are completed.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of artificial intelligence, and particularly relates to a multi-platform distributed cloud organization integrated simulation system and method. BACKGROUND

[0002] The system-level comprehensive task system architecture is complex, and not only the utility and efficiency of a single platform need to be considered, but also the multi-platform cooperation needs to be considered. Under the background of sea-air cooperation, each ship and aircraft has an independent interface, resulting in a large increase in cost and more complex system operation. Therefore, a multi-platform cooperation method needs to be found to efficiently integrate resources and fully exert the advantages of various units. SUMMARY

[0003] The application provides a multi-platform distributed cloud organization integrated simulation system and method, and the system is built according to the multi-platform distributed cloud organization concept, scene design and DoDAF-based multi-platform distributed cloud organization system architecture design, and the running process and decision of the multi-platform distributed cloud organization are completed.

[0004] The application is implemented by the following technical scheme:

[0005] The application relates to a multi-platform distributed cloud organization integrated architecture simulation system, which comprises a running process subsystem and a decision subsystem, wherein: the running process subsystem simulates cloud nodes, node dynamic cloud access, resource pooling, resource pool scheduling, scale dynamic expansion and human-computer interaction processes in a typical application process of the multi-platform distributed cloud organization; and the decision subsystem performs decision processes.

[0006] The multi-platform distributed cloud organization refers to an application system based on a cloud architecture, which is formed by organizing resources in various units and is supported by cloud computing, big data and artificial intelligence technology, and has the characteristics of dynamic access, resource pooling, scheduling and on-demand service cloud, and the elasticity is reflected in the aspects of scale scalability, network resilience, heterogeneous operation and evolvability.

[0007] The integrated architecture refers to a dynamic and centerless multi-platform distributed cloud organization system architecture. The multi-platform distributed cloud organization integrated architecture technology is used for adaptive and elastic changes, and ensures that the task is dynamically and autonomously completed.

[0008] The dynamic refers to: in the multi-platform distributed cloud organization architecture, each unit establishes the task processing mode of each unit according to the physical resource equipment capacity of the unit for the unit task demand. These units support the completion of the task of the unit on the one hand, and in the capacity of abundance or in the interval of executing the task cycle of the unit, can provide capacity support for other units under the cloud organization and management.

[0009] The centerless refers to: the multi-platform distributed cloud organization system is dispersed on different units to meet the security capacity and distributed connection according to the system equipment distribution organization mode according to the system resident distribution function capacity demand.

[0010] The cloud node refers to a basic computing unit in cloud computing, which is a virtual entity created on a cloud platform through virtualization technology, and can dynamically configure computing power, storage and network resources. In the present application, it refers to a platform that has entered the cloud and carries detection resources, positioning resources, tracking resources and indication resources.

[0011] The node dynamic cloud refers to the process of the platform changing to join the multi-platform distributed cloud organization according to the decision result.

[0012] The resource pooling refers to a resource configuration mechanism, which involves centralized management of different types of resources, and dynamically allocates different use scenarios according to the demand, so as to improve the utilization rate and management efficiency of resources. In the present application, it refers to the division of different resources into detection, positioning, tracking and indication resource pools according to their own characteristics.

[0013] The resource pool scheduling refers to arranging the resources in the detection, positioning, tracking and indication resource pools to perform corresponding tasks according to the decision result.

[0014] The scale dynamic stretching refers to meeting the user demand by increasing / decreasing nodes, and then improving the service ability of the cloud computing system.

[0015] The human-computer interaction process is the information transmission and conversion process between man and computer through the intermediary of the multi-platform distributed cloud organization simulation user interface.

[0016] The simulation refers to reproducing the essential process occurring in the actual multi-platform distributed cloud organization system by using a model, and studying the multi-platform distributed cloud organization system through experiments on the system model.

[0017] The decision-making process refers to the whole process of determining the task target, selecting the optimal task scheme, and proposing the optimal task scheme.

[0018] The operation process subsystem comprises a cloud node simulation module, a node dynamic cloud entry simulation module, a resource pooling simulation module, a resource scheduling simulation module, a scale dynamic expansion simulation module and a man-machine interaction interface module.

[0019] The decision subsystem comprises a model construction module and a resource dynamic allocation module.

[0020] The application relates to a simulation method based on the above system, and the multi-platform distributed cloud organization integrated simulation system can realize simulation verification of a resource cloud entry process of a multi-platform distributed cloud organization architecture, and can perform resource dynamic allocation in target interception and support resource scheduling processes.

[0021] The resource refers to resources that can be used by commanders in a distributed environment, and the resources can be entity resources such as aircrafts and ships or information resources such as situation information, command information (orders, plans) and decision information.

[0022] The scheduling refers to the following aspects: constructing a deep learning model suitable for the resource dynamic scheduling requirements of a multi-platform distributed cloud organization application process, realizing resource dynamic allocation in target interception and supporting resource scheduling process implementation schemes. Technical effects

[0023] Compared with the prior art, the application places cloud architecture verification on a simulation verification platform, faces future deep sea ZZ requirements, aims at TXYZZ concepts, takes typical task operation as a main background, completes TXY operation process demonstration and TXY intelligent decision demonstration, has certain dynamic nature, and visualizes the access of resources in an elastic cloud architecture. The application solves the problem that the existing cloud architecture only realizes data transmission between units through network connection, and lacks a simulation verification tool for operations under the cloud architecture. BRIEF DESCRIPTION OF DRAWINGS

[0024] Figure 1 It is a method flowchart of the application;

[0025] Figure 2 It is a system module block diagram of the application;

[0026] Figure 3 It is an organization architecture diagram of the application;

[0027] Figure 4 It is an embodiment effect schematic diagram of the application;

[0028] Figure 5 It is an operation flowchart of the cloud node simulation module;

[0029] Figure 6 It is an operation flowchart of the node dynamic cloud entry simulation module;

[0030] Figure 7 is a flow chart of the operation of the scale dynamic scaling simulation module;

[0031] Figure 8 is a flow chart of the operation of the resource pooling simulation module;

[0032] Figure 9 is a flow chart of the operation of the resource scheduling simulation module;

[0033] Figure 10 is a flow chart of the operation of the human-computer interaction interface module. DETAILED DESCRIPTION

[0034] As shown in Figure 1 , a flow chart of the multi-platform distributed cloud organization integrated simulation method of the embodiment is shown. After the simulation starts, the scene model transmits battlefield situation data to the running process subsystem in the multi-platform distributed cloud organization integrated simulation system, and the decision subsystem completes algorithm decision. In the running process subsystem, cloud node management, cloud node dynamic entry into the cloud, cloud node dynamic scaling, resource pooling, resource pool scheduling management, and damage chain construction simulation are performed. The simulation is paused / ended.

[0035] As shown in Figure 2 , a block diagram of the multi-platform distributed cloud organization integrated simulation system of the embodiment is shown. The multi-platform distributed cloud organization integrated simulation system includes a running process subsystem and a decision subsystem. The running process subsystem simulates node dynamic entry into the cloud, resource pooling, resource pool scheduling, scale dynamic scaling, and human-computer interaction process in the typical aspects of the multi-platform distributed cloud organization battle process. The decision subsystem makes decisions. The multi-platform distributed cloud organization integrated simulation system receives model linkage data input by the architecture dynamic executable model and the scene model that meet the scene and requirements, and performs simulation and decision.

[0036] As shown in Figure 3 , an internal organization architecture of the embodiment is shown. It is divided into three layers of task, function, and resource. In the task layer, according to application requirements, combined with the resource and function capability in the system, the requirements are gradually decomposed to the application unit resource and function with corresponding capabilities. Then, based on the task plan, according to the current resource, function capability, and the entire system running state, the appropriate application unit sequence is selected in real time to execute the task, that is, task synthesis. In the function layer, facing the application task requirements, based on the function execution rules and the function pool that can support the application task capability, different function sequences are dynamically and flexibly generated. Function execution is a process of executing function capability in real time according to the application organization mode based on the application unit and application resource capability state. In the resource pool, facing the function capability requirements, the appropriate resources are selected and scheduled from the currently registered resources to provide performance capability, ensuring that the application capability requirements are met.

[0037] As shown in Figure 4The diagram shown is a schematic representation of an embodiment of the present invention. The system includes a resource pool interface, a resource connection visualization interface, a resource information interface, a key parameter interface, and a log interface.

[0038] like Figure 5 As shown, the cloud node simulation module refers to the module that displays cloud node information during the simulation process, including cloud node framework hierarchy, composition method, master node parameters, and unit parameters.

[0039] like Figure 6 As shown, the node dynamic cloud entry simulation module refers to the module that displays the dynamic cloud entry process of the unit, and can support the dynamic cloud entry process of one node in each of the five typical space domains: land, sea, air, space, and submarine.

[0040] like Figure 7 As shown, the aforementioned dynamic scaling simulation module refers to a module that reflects the elastic scaling process of a dynamic, decentralized, multi-platform distributed cloud organization system during the dynamic entry and exit of nodes into and out of the cloud. It supports dynamic scaling of node size from 1 to 100.

[0041] like Figure 8 As shown, the resource pooling simulation module refers to a module that pools units and displays resource information for each resource pool, including unit name and scheduling status. It supports four types of resource pooling management processes: detection, location, tracking, and indication.

[0042] like Figure 9 As shown, the resource scheduling simulation module refers to a module that, in response to application needs in air, sea, underwater, and land applications, detects, locates, tracks, and indicates resource categories from the resource pool, and displays the resource scheduling process.

[0043] like Figure 10 As shown, the human-computer interaction interface module is designed to facilitate operators in switching between different modules and to enable other personnel to receive relevant information.

[0044] The decision-making subsystem manages the decision-making process and includes a backend model building module and a frontend dynamic resource allocation module. Addressing application needs in air, sea, underwater, and land environments, the subsystem displays the resource scheduling process, from resource pool scheduling detection, location, tracking, and indication of resource categories.

[0045] This embodiment relates to a simulation operation method for the above system, including the following steps:

[0046] Step one: the architecture linkage software sends a start control instruction, controls the system architecture design model and the scene model simulation start; the scene model sends the battlefield situation data to the running process subsystem in real time according to the battlefield situation, the running process subsystem receives the situation data and sends to the decision subsystem; the decision subsystem makes a decision based on the decision model, and sends the control instruction to the running process subsystem and the scene model;

[0047] Step two: the scene model receives the real-time control instruction sent by the decision subsystem, controls the behavior and task of the force in the scene model in real time according to the decision instruction, the running process subsystem receives the real-time instruction sent by the decision subsystem, controls the cloud node and resource scheduling, completes the cloud node dynamic cloud entering, cloud node dynamic expansion and resource pool scheduling process;

[0048] Step three: the architecture linkage software controls the cooperative simulation process of the architecture dynamic executable model and the scene model, controls the pause and stop of the cooperative simulation.

[0049] The resource pool scheduling management refers to the allocation of tasks and node resources for different events and battlefield situations.

[0050] According to the above improvements, the multi-platform distributed cloud organization integrated simulation system first supports cloud node dynamic expansion according to the characteristics of cloud node dynamic expansion, can carry out the dynamic cloud entering process of five typical spatial domain nodes; secondly, according to the characteristics of the resource pooling of the multi-platform distributed cloud organization, the four types of resource pooling management processes of detection, positioning, tracking and indication can be realized; finally, according to the characteristics of the multi-platform distributed cloud organization scheduling, a suitable deep learning model is constructed to realize the dynamic allocation of resources and support the resource scheduling process.

[0051] Compared with the prior art, the cloud architecture verification is put on the simulation verification platform, the future application demand is faced, the multi-platform distributed cloud organization concept is aimed at, the typical aspect task operation is taken as the main background, the multi-platform distributed cloud organization running process and the multi-platform distributed cloud organization decision are completed, it has certain dynamic, the access situation of the resources in the multi-platform distributed cloud organization architecture is visualized.

[0052] The above specific implementation can be adjusted in different ways by those skilled in the art without departing from the principles and purposes of the present application, the protection scope of the present application is subject to the claims and is not limited by the above specific implementation, each implementation scheme within the scope is subject to the constraint of the present application.

Claims

1. A multi-platform distributed cloud organization integration architecture simulation system, characterized in that, The application relates to an integrated simulation system of a multi-platform distributed cloud organization, and belongs to the technical field of cloud computing. The integrated simulation system comprises a running process subsystem and a decision-making subsystem, wherein: the running process subsystem simulates cloud nodes, node dynamic cloud entry, resource pooling, resource pool scheduling, scale dynamic expansion and man-machine interaction processes in a typical application process of the multi-platform distributed cloud organization; and the decision-making subsystem carries out decision-making processes. The multi-platform distributed cloud organization refers to an application system based on a cloud architecture, which is formed by organizing resources in units and aims to realize efficient release of application efficiency, supports dynamic entry and exit of various units in land, sea, air, space and submarine domains, and has dynamic access, resource pooling, scheduling and on-demand service cloud characteristics. The integrated architecture refers to a dynamic and centerless multi-platform distributed cloud organization system architecture. The dynamic refers to that, in the multi-platform distributed cloud organization architecture, each unit establishes a task processing mode of each unit according to unit physical resource equipment capacity and unit task requirements; and these units support the completion of tasks of the units, and provide capacity support for other units under the cloud organization and management in the capacity surplus or in the interval of the execution of the unit task cycle.

2. The multi-platform distributed cloud organization integration architecture simulation system according to claim 1, characterized in that, The running process subsystem comprises a cloud node simulation module, a node dynamic cloud entry simulation module, a resource pooling simulation module, a resource scheduling simulation module, a scale dynamic expansion simulation module and a man-machine interaction interface module. The decision-making subsystem comprises a model construction module and a resource dynamic allocation module.

3. A simulation method based on the system of claim 1 or 2, characterized by, The integrated simulation system of the multi-platform distributed cloud organization can realize simulation verification of resource cloud entry processes of the multi-platform distributed cloud organization architecture, and carries out resource dynamic allocation in target interception and supports resource scheduling processes. The resource refers to resources that can be used by commanders in a distributed environment, and the resources can be physical resources such as aircraft, ships or information resources and decision-making information. The scheduling refers to that, according to resource dynamic scheduling requirements in the application process of the multi-platform distributed cloud organization, a deep learning model is constructed, resource dynamic allocation in target interception is realized, and a resource scheduling process implementation scheme is supported.

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