为了加快配电网系统的数据处理效率,本研究在配电网信息物理系统中应用边缘计算技术,在数据源的一端就近提供计算服务,具有反馈环节使物理系统与信息系统之间紧密联系。提出协作式边缘计算资源的优化配置策略,将系统业务请求和计算任务分给其他边缘节点和云数据中心,协调器根据网络的资源分配决策变量执行优化分配;对信息系统中的脆弱点进行识别,基于配电网的拓扑特性和攻击路径建立多层拓扑模型,计算信息节点的脆弱度,遍历所有的攻击路径识别脆弱点。实验结果表明,本研究配电网信息物理系统识别到的脆弱点数据量最大(超出5 000),边缘计算的分载量最高达到1.42 FLOP。
Abstract
In order to speed up the data processing efficiency of the distribution network system,the edge computing technology is applied in the distribution network information physical system.The data computing service is provided at the nearest end of the data source,and the feedback link makes the physical system and the information system closely connected.An optimal allocation strategy of collaborative edge computing resources is proposed,in which the system business requests and computing tasks are distributed to other edge nodes and cloud data centers,and the coordinator performs optimal allocation according to the decision variables of network resource allocation.To identify the vulnerable points in the information system,establish a multi-layer topology model based on the topological characteristics of the distribution network and attack path,calculate the vulnerability of information nodes,and identify the vulnerable points by traversing all attack paths.The experiment results show that the data volume of vulnerable points identified by the distribution network information physical system in this study is the largest,the data volume exceeds 5 000,and the load of edge calculation reaches the highest 1.42 FLOP.
关键词
边缘计算技术 /
决策变量 /
脆弱点识别 /
多层拓扑模型
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Key words
edge computing technology /
decision variables /
identification of vulnerable points /
multilayer topological model
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中图分类号：
TP37
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脚注
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基金
*国家自然科学基金资助项目(61832005)。
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