一种资源受限的时延与能耗优化卸载策略

打开文本图片集

关键词：边缘计算；多点协作传输；vogel；任务卸载；迁移成本

中图分类号：TP393.01 文献标志码：A 文章编号：1671-6841（2025）05-0062-07

DOI：10.13705/j. issn.1671-6841.2023262

Abstract： Ofload decision-making was an important part of data processing. However，most studies ignored the delay and energy consumption generated by collboration between edge servers when determining offload decisions. An algorithm to minimize task processing costs was proposed，to achieve the goals of optimizing costs by minimizing the delay and energy consumption generated during task migration and determining the optimal ofload ratio of sensed data between the cloud and the edge.Firstly，the optimization objective was transformed into a transportation problem with balanced production and sales，and the Vogel algorithm was used to solve the minimum delay and energy consumption of task processing at the edge.Secondly，combined with the delay and energy consumption of task processing in the cloud and the edge，the optimal offloading ratio was solved to minimize the costs of task processing.Finally，Matlab simulation experiments showed that the proposed algorithm reduces the task processng cost by about 18% （20 to 25% compared with other algorithms.

Key words： edge computing； multipoint cooperative transmision; vogel; task offloading； migration costs

0 引言

（mobileedgecomputing，MEC）通过将物联网等应用程序部署到距离用户更近的边缘服务器中，可以有效降低访问时延与能耗。（剩余11172字）