摘要
边缘计算技术为计算密集型业务提供了一种新型的低时耗、低能耗、数据安全、实时性高的数据处理方案。在面对数量庞大的电机故障信息时,边缘计算能有效解决电机故障数据处理花费高、数据泄露、实时性差等问题。根据数据源分布特点,充分考虑边缘服务器(Edge Server,ES)、云服务器计算负载以及任务传输时耗,设计了基于端边协同的多边缘服务器并行任务处理框架。在此框架下对最短时耗及最低能耗进行了研究分析,充分优化任务执行时间以及能耗表现。
Edge computing technology provides a new type of data processing solution with low time consumption, low energy consumption, secure data and high real-time performance for computing-intensive services. In the face of a large number of motor fault information, edge computing can effectively solve the problems of high cost of motor fault data processing, data leakage, and poor real-time performance. According to the distribution characteristics of data sources, fully considering the edge server, cloud server computing load as well as task transmission time consumption, a parallel task processing framework of multi-edge server based on end-edge collaboration is designed. In this framework, the shortest time consumption and the lowest energy consumption are studied and analyzed to fully optimize the task execution time and energy consumption performance.
作者
潘显斌
孙康
徐震
Pan Xianbin;Sun Kang;Xu Zhen(School of Mechanical and Automotive Engineering,Shanghai University of Engineering Science,Shanghai 200000,China)
出处
《计算机时代》
2022年第10期69-72,76,共5页
Computer Era
基金
国家自然科学基金项目(11604203)。
关键词
边缘计算
端边协同
并行计算
故障分析
edge computing
end-edge collaboration
parallel computing
fault analysis
作者简介
潘显斌(1996-),男,安徽省六安市人,硕士研究生,主要研究方向:工业物联网;通讯作者:徐震(1984-),男,山东聊城人,博士,讲师,主要研究方向:人工智能物联网。
