Joint Computation Offloading and Resource Optimization for Minimizing Network-Wide Energy Consumption in Ultradense MEC Networks

IF 4 3区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS IEEE Systems Journal Pub Date : 2024-04-29 DOI:10.1109/JSYST.2024.3391811
Tianqing Zhou;Dong Qin;Xuefang Nie;Xuan Li;Nan Jiang;Chunguo Li
{"title":"Joint Computation Offloading and Resource Optimization for Minimizing Network-Wide Energy Consumption in Ultradense MEC Networks","authors":"Tianqing Zhou;Dong Qin;Xuefang Nie;Xuan Li;Nan Jiang;Chunguo Li","doi":"10.1109/JSYST.2024.3391811","DOIUrl":null,"url":null,"abstract":"In this article, the orthogonal frequency-division multiple access (OFDMA) integrated with frequency spectrum (band) partitioning and equal bandwidth allocation is first introduced to mitigate the complicated, severe, and average network interferences in ultradense mobile edge computing (MEC) networks. Then, under such OFDMA, the system energy consumed by all users [mobile devices (MDs)] and base stations (BSs) is minimized to reduce the huge energy consumed by ultradense small BSs (SBSs) and prolong the standby time of MDs, jointly optimizing the spectrum partitioning factor, local and remote computation capacities, local power, and binary offloading decision. According to the coupling form of optimization parameters in the formulated problem, this problem is first cut into a joint power control and resource (frequency spectrum) partitioning (PCRP) subproblem, a joint user association, and a computation capacity optimization (UACCO) subproblem. Then, we try to design an effective iteration algorithm to attain the solutions to these problems using convex optimization methods. As for this algorithm, we give some detailed convergence, computation complexity, and simulation analyses. The simulation results show that it may achieve a guaranteed offloading performance and lower energy consumption than other existing algorithms.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"18 2","pages":"1115-1126"},"PeriodicalIF":4.0000,"publicationDate":"2024-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Systems Journal","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10509708/","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0

Abstract

In this article, the orthogonal frequency-division multiple access (OFDMA) integrated with frequency spectrum (band) partitioning and equal bandwidth allocation is first introduced to mitigate the complicated, severe, and average network interferences in ultradense mobile edge computing (MEC) networks. Then, under such OFDMA, the system energy consumed by all users [mobile devices (MDs)] and base stations (BSs) is minimized to reduce the huge energy consumed by ultradense small BSs (SBSs) and prolong the standby time of MDs, jointly optimizing the spectrum partitioning factor, local and remote computation capacities, local power, and binary offloading decision. According to the coupling form of optimization parameters in the formulated problem, this problem is first cut into a joint power control and resource (frequency spectrum) partitioning (PCRP) subproblem, a joint user association, and a computation capacity optimization (UACCO) subproblem. Then, we try to design an effective iteration algorithm to attain the solutions to these problems using convex optimization methods. As for this algorithm, we give some detailed convergence, computation complexity, and simulation analyses. The simulation results show that it may achieve a guaranteed offloading performance and lower energy consumption than other existing algorithms.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
联合计算卸载和资源优化,最大限度降低超密集 MEC 网络的全网能耗
本文首先介绍了正交频分多址(OFDMA)与频谱(频段)划分和等带宽分配相结合的方法,以减轻超密集移动边缘计算(MEC)网络中复杂、严重和平均的网络干扰。然后,在这种 OFDMA 下,通过联合优化频谱划分因子、本地和远程计算能力、本地功率和二进制卸载决策,使所有用户(移动设备(MD))和基站(BS)消耗的系统能量最小化,从而减少超密集小型基站(SBS)消耗的巨大能量,延长 MD 的待机时间。根据所提问题中优化参数的耦合形式,首先将该问题切割为联合功率控制和资源(频谱)分配(PCRP)子问题、联合用户关联和计算能力优化(UACCO)子问题。然后,我们尝试设计一种有效的迭代算法,利用凸优化方法获得这些问题的解决方案。对于该算法,我们给出了一些详细的收敛性、计算复杂度和仿真分析。仿真结果表明,与其他现有算法相比,该算法可以实现有保证的卸载性能和更低的能耗。
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 去求助
来源期刊
IEEE Systems Journal
IEEE Systems Journal 工程技术-电信学
CiteScore
9.80
自引率
6.80%
发文量
572
审稿时长
4.9 months
期刊介绍: This publication provides a systems-level, focused forum for application-oriented manuscripts that address complex systems and system-of-systems of national and global significance. It intends to encourage and facilitate cooperation and interaction among IEEE Societies with systems-level and systems engineering interest, and to attract non-IEEE contributors and readers from around the globe. Our IEEE Systems Council job is to address issues in new ways that are not solvable in the domains of the existing IEEE or other societies or global organizations. These problems do not fit within traditional hierarchical boundaries. For example, disaster response such as that triggered by Hurricane Katrina, tsunamis, or current volcanic eruptions is not solvable by pure engineering solutions. We need to think about changing and enlarging the paradigm to include systems issues.
期刊最新文献
Relationship between emotional state and masticatory system function in a group of healthy volunteers aged 18-21. Table of Contents Front Cover Editorial IEEE Systems Council Information
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1