{"title":"Computation Rate Optimization for RIS-Assisted Multi-server MEC System","authors":"Chen Liu, Wensheng Zhang, Yongwei Wang","doi":"10.1109/ICECE56287.2022.10048627","DOIUrl":null,"url":null,"abstract":"Reconfigurable intelligent surface (RIS) is an emerging technology that enables intelligent control of wireless communication environment. In this paper, an RIS-assisted multi-server mobile edge computing (MEC) system is studied. By jointly optimizing the offloading power, offloading time, central processing unit (CPU) frequency, RIS phase shift, and MEC server allocation of each device, the maximum sum computation rate of the system is achieved. A greedy-based algorithm is used to tackle the server allocation problem. The simulation results demonstrate that the computation rate is improved by applying RIS into the MEC system, and it can be further improved by deploying more MEC servers with proper server allocation strategy.","PeriodicalId":358486,"journal":{"name":"2022 IEEE 5th International Conference on Electronics and Communication Engineering (ICECE)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 5th International Conference on Electronics and Communication Engineering (ICECE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICECE56287.2022.10048627","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Reconfigurable intelligent surface (RIS) is an emerging technology that enables intelligent control of wireless communication environment. In this paper, an RIS-assisted multi-server mobile edge computing (MEC) system is studied. By jointly optimizing the offloading power, offloading time, central processing unit (CPU) frequency, RIS phase shift, and MEC server allocation of each device, the maximum sum computation rate of the system is achieved. A greedy-based algorithm is used to tackle the server allocation problem. The simulation results demonstrate that the computation rate is improved by applying RIS into the MEC system, and it can be further improved by deploying more MEC servers with proper server allocation strategy.
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