Preference-based and Homogeneous Coalition Formation in Fog Computing

M. Sharaf, T. El-Ghazawi
{"title":"Preference-based and Homogeneous Coalition Formation in Fog Computing","authors":"M. Sharaf, T. El-Ghazawi","doi":"10.1109/CSCN.2019.8931361","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a Markov Chain Monte Carlo (MCMC) algorithm to handle fog nodes coalition formation problem. The need to construct coalitions emanates from the fact that some nodes could not be able to handle the required computation on its own due to their limited computational capabilities. Also, we introduce a set of constraints on the formed coalitions. Specifically, nodes could have preferences with whom to coalesce. Even more the formed coalitions have to be of semi-equal computational powers.","PeriodicalId":102095,"journal":{"name":"2019 IEEE Conference on Standards for Communications and Networking (CSCN)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE Conference on Standards for Communications and Networking (CSCN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSCN.2019.8931361","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

In this paper, we propose a Markov Chain Monte Carlo (MCMC) algorithm to handle fog nodes coalition formation problem. The need to construct coalitions emanates from the fact that some nodes could not be able to handle the required computation on its own due to their limited computational capabilities. Also, we introduce a set of constraints on the formed coalitions. Specifically, nodes could have preferences with whom to coalesce. Even more the formed coalitions have to be of semi-equal computational powers.
基于偏好和均匀的雾计算联盟形成
本文提出了一种马尔可夫链蒙特卡罗(MCMC)算法来处理雾节点联盟形成问题。构建联盟的需求源于这样一个事实,即由于某些节点的计算能力有限,它们无法自己处理所需的计算。此外,我们还引入了一组对形成的联盟的约束。具体来说,节点可以有与谁合并的偏好。更重要的是,形成的联盟必须具有半相等的计算能力。
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