Topology Aware Cluster Configuration for Minimizing Communication Delay in Edge Computing

K. Rajashekar, Souradyuti Paul, S. Karmakar, Subhajit Sidhanta
{"title":"Topology Aware Cluster Configuration for Minimizing Communication Delay in Edge Computing","authors":"K. Rajashekar, Souradyuti Paul, S. Karmakar, Subhajit Sidhanta","doi":"10.1109/ICDCS54860.2022.00144","DOIUrl":null,"url":null,"abstract":"For real-time edge computing applications working under stringent deadlines, communication delay between IoT devices and edge devices needs to be minimized. Since the generalized assignment problem being NP-Hard, an optimal assignment of IoT devices to the edge cluster is hard. We propose the application RL based heuristics to obtain a near-optimal assignment of IoT devices to the edge cluster while ensuring that none of the edge devices are overloaded. We demonstrate that our algorithm outperforms the state-of-the-art.","PeriodicalId":225883,"journal":{"name":"2022 IEEE 42nd International Conference on Distributed Computing Systems (ICDCS)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","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/ICDCS54860.2022.00144","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

For real-time edge computing applications working under stringent deadlines, communication delay between IoT devices and edge devices needs to be minimized. Since the generalized assignment problem being NP-Hard, an optimal assignment of IoT devices to the edge cluster is hard. We propose the application RL based heuristics to obtain a near-optimal assignment of IoT devices to the edge cluster while ensuring that none of the edge devices are overloaded. We demonstrate that our algorithm outperforms the state-of-the-art.
基于拓扑感知的集群配置,最小化边缘计算中的通信延迟
对于在严格期限下工作的实时边缘计算应用,需要最大限度地减少物联网设备和边缘设备之间的通信延迟。由于广义分配问题是NP-Hard问题,物联网设备到边缘集群的最优分配是困难的。我们提出了基于强化学习的应用启发式方法,以获得物联网设备到边缘集群的近乎最优分配,同时确保没有任何边缘设备过载。我们证明了我们的算法优于最先进的算法。
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:481959085
Book学术官方微信