边缘计算环境下服务质量可信的任务迁移节点选择

Task Migration Node Selection with Reliable Service Quality in Edge Computing Environment

随着物联网、大数据和5G网络的快速发展及应用,传统的云计算模式已无法高效处理网络边缘设备所产生的海量计算任务,边缘计算应运而生。边缘计算环境下,计算任务将被迁移到接近数据源的计算设备上执行,这为拓展终端节点资源以及缓解云中心负载提供了新的解决方案。现有的任务迁移决策均是在任务迁移节点确定的前提下制定的,并未考虑存在多个任务迁移节点可选的情景,而边缘计算下任务迁移节点的选择直接影响着任务迁移的服务质量,因此文中构建了服务质量可信模型,分别从时间可信、行为可信、资源可信3个维度对任务迁移节点进行评价。为了解决任务迁移节点数量巨大带来的选择效率低的问题,采用基于聚类编码的skyline查询算法对任务迁移节点进行筛选,并利用灰色关联分析法进行任务迁移节点的最终选择。实验结果表明,所提基于服务质量可信的任务迁移节点选择策略的任务迁移成功率平均提高了36%,任务完成吞吐量平均提高了18%。

With the rapid development and wide application of the Internet of things,big data and 5G network,the traditional cloud computing mode has been unable to efficiently handle the massive computing tasks generated by network edge devices,so edge computing came into being.Computing tasks in edge computing environments will be migrated to computing devices close to data sources for execution,providing new solutions for expanding terminal node resources and alleviating cloud center load.The existing task migration decisions are made on the premise that the task migration node is determined,without considering the si-tuation that multiple task migration nodes are available.The selection of the task migration node in edge computing directly affects the service quality of task migration,so,in this paper,a service quality trust model is constructed to evaluate the task migration nodes from three dimensions:time trust,behavior trust and resource trust.In order to avoid the problem of low selection efficiency caused by the large number of task migration nodes,a skyline query algorithm based on cluster coding is adopted to screen the task migration nodes,and grey relative analysis is used for the final selection of task migration nodes.The experimental results show that the proposed task migration node selection strategy based on reliable service quality can increase the success rate of task migration by 36%and the throughput of task completion by 18%on average.