Zhenyu Zhang, Huan Zhouand, Liang Zhao, Victor C. M. Leung
{"title":"Digital Twin Assisted Computation Offloading and Service Caching in Mobile Edge Computing","authors":"Zhenyu Zhang, Huan Zhouand, Liang Zhao, Victor C. M. Leung","doi":"10.1109/ICDCS54860.2022.00140","DOIUrl":null,"url":null,"abstract":"This paper considers the joint optimization of computation offloading, service caching, and resource allocation in the Digital Twin Edge Network (DTEN), and formulates the problem as Mixed-Integer Non-Linear Programming (MINLP), whose goal is to minimize the long-term energy consumption of the system. To solve the optimization problem, a Deep Deterministic Policy Gradient (DDPG) based algorithm is proposed for determining the strategies of computation offloading, service caching, and resource allocation. Simulation results demonstrate that the proposed DDPG based algorithm can reduce the long-term energy consumption of the system greatly, and outperform other benchmark algorithms under different scenarios.","PeriodicalId":225883,"journal":{"name":"2022 IEEE 42nd International Conference on Distributed Computing Systems (ICDCS)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 42nd International Conference on Distributed Computing Systems (ICDCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDCS54860.2022.00140","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper considers the joint optimization of computation offloading, service caching, and resource allocation in the Digital Twin Edge Network (DTEN), and formulates the problem as Mixed-Integer Non-Linear Programming (MINLP), whose goal is to minimize the long-term energy consumption of the system. To solve the optimization problem, a Deep Deterministic Policy Gradient (DDPG) based algorithm is proposed for determining the strategies of computation offloading, service caching, and resource allocation. Simulation results demonstrate that the proposed DDPG based algorithm can reduce the long-term energy consumption of the system greatly, and outperform other benchmark algorithms under different scenarios.