A Dynamic Task Impact Estimation Method Based on Adaptive Switching Bayesian Networks

Abstract

The invention discloses a method for estimating the impact of a dynamic task on an adaptive switching Bayesian network. Through distributed tracking of service calls, the internal dependencies of the service domain are automatically generated; the service domain is used as a medium to map upwards and downwards respectively. Generate the internal dependencies of task domain and resource domain; according to the multi-attribute group description of tasks, services and resources, build an association model of task domain-service domain-resource domain; use the dependency characteristics of the association model to establish a Bayesian network; for The time-varying characteristics of task domain-service domain-resource domain dependencies during system operation, build association models and Bayesian network libraries, and adaptively switch network models according to actual resource scheduling strategies; use prior test data to train Bayesian Network, combined with actual monitoring status data, for dynamic task impact estimation.

Description

technical field [0001] The invention relates to the technical field of information systems, in particular to a method for estimating the dynamic task impact of an adaptive switching Bayesian network. Background technique [0002] When the system suffers from external attacks or internal disturbances, how to ensure the smooth completion of ongoing tasks in the system is still a challenge. Cyber ​​attacks may seriously affect mission status, mission progress, and mission completion, and may even cause mission failure. When a system is attacked, the operational commander's greatest concern is the possibility of mission completion and the degree to which the mission is affected. The task impact estimation method is to complete this function. According to the system node status fed back by the monitoring system, the impact estimation is performed on the final task, which provides a reference for the decision-making of the combat commander and the maintenance of the system suppor...

AI Technical Summary

Problems solved by technology

The method based on the situational knowledge reference model (SKRM) can realize task impact estimation, but because it does not strictly stipulate cross-layer interconnection, SKRM lacks the ability to conduct quantitative task impact analysis

Using the Impact Dependency Graph (IDG) for impact assessment can calculate the degree of task impact to a certain extent, but it does not give a detailed method for generating dependencies in the IDG graph, and the calculation method of the logical relationship between nodes also affects the accuracy of its assessment sex

[0004] Most of the existing task impact estimation methods are qualitative evaluation methods of modeling, and methods that can achieve accurate quantitative evaluation are relatively rare, and the current methods are all for static task impact estimation.

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