Energy-Efficient Resource Allocation for Wireless Powered Cognitive Mobile Edge Computing

Boyang Liu, Jing Bai, Yujiao Ma, Jin Wang, G. Lu
{"title":"Energy-Efficient Resource Allocation for Wireless Powered Cognitive Mobile Edge Computing","authors":"Boyang Liu, Jing Bai, Yujiao Ma, Jin Wang, G. Lu","doi":"10.1109/ICCW.2019.8756664","DOIUrl":null,"url":null,"abstract":"In this paper, a framework for mobile edge computing (MEC) in cognitive radio (CR) networks is proposed, which integrates three technologies: MEC, cooperative relaying and wireless power transfer (WPT). The purpose of this paper is to minimize the energy cost of the WD in both partial offloading and local computing scenarios. A two-phase algorithm is proposed to solve the optimization problems. Semi-closed and closed-form solutions are derived by using Lagrangian dual decomposition and successive pseudo-convex approximation (SPCA) algorithm. Simulation results show the effects of the different parameters on the system performance and demonstrate the validity of our proposed algorithm.","PeriodicalId":426086,"journal":{"name":"2019 IEEE International Conference on Communications Workshops (ICC Workshops)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE International Conference on Communications Workshops (ICC Workshops)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCW.2019.8756664","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

In this paper, a framework for mobile edge computing (MEC) in cognitive radio (CR) networks is proposed, which integrates three technologies: MEC, cooperative relaying and wireless power transfer (WPT). The purpose of this paper is to minimize the energy cost of the WD in both partial offloading and local computing scenarios. A two-phase algorithm is proposed to solve the optimization problems. Semi-closed and closed-form solutions are derived by using Lagrangian dual decomposition and successive pseudo-convex approximation (SPCA) algorithm. Simulation results show the effects of the different parameters on the system performance and demonstrate the validity of our proposed algorithm.
基于无线供电认知移动边缘计算的节能资源分配
本文提出了一种基于认知无线电(CR)网络的移动边缘计算(MEC)框架,该框架融合了MEC、协同中继和无线功率传输(WPT)三种技术。本文的目的是在局部卸载和局部计算场景下最小化WD的能源成本。提出了一种求解优化问题的两阶段算法。利用拉格朗日对偶分解和逐次伪凸逼近(SPCA)算法,导出了半闭解和闭解。仿真结果显示了不同参数对系统性能的影响,验证了算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信