物联网学报2024，Vol.8Issue(2)：91-102,12.DOI:10.11959/j.issn.2096-3750.2024.00361
基于能量收集技术的协作卸载计算方案
Collaborative offloading computing scheme based on energy harvesting technology
摘要
Abstract
In recent years,the energy requirements for devices in internet of things(IoT)applications have increased,making energy harvesting(EH)technology an important way to alleviate the energy shortage problem in edge computing and extend the battery life of devices.However,when there was insufficient renewable energy in the environment,the depletion of device power can cause task interruption and affect the performance of IoT.To solve this problem,a task offloading framework that combined energy harvesting and device-to-device(D2D)communication technology was pro-posed,using a deep reinforcement learning(DRL)-based edge collaborative offloading computing scheme to make au-tonomous decisions and solve resource allocation problems using simulated annealing algorithms to minimize the total cost of system operation.Simulation results on stable and extreme energy environments show that the proposed scheme can run stably and cost-effectively in single-user multiple-device scenarios.关键词
边缘计算/能量收集/设备间通信/深度强化学习Key words
edge computing/energy harvesting/device-to-device communication/deep reinforcement learning分类
信息技术与安全科学引用本文复制引用
王珺,赵浩东..基于能量收集技术的协作卸载计算方案[J].物联网学报,2024,8(2):91-102,12.基金项目
江苏省研究生科研与实践创新计划项目(No.46006CX21732) （No.46006CX21732）
江苏省重点研发计划(No.BE2020084-5) Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.46006CX21732),Jiangsu Pro-vincial Key Research and Development Program(No.BE2020084-5) （No.BE2020084-5）
