基于雾计算的移动性和资源管理,实现弹性移动网络

IF 3.2 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS High-Confidence Computing Pub Date : 2023-11-24 DOI:10.1016/j.hcc.2023.100193
Hang Zhao, Shengling Wang, Hongwei Shi
{"title":"基于雾计算的移动性和资源管理,实现弹性移动网络","authors":"Hang Zhao,&nbsp;Shengling Wang,&nbsp;Hongwei Shi","doi":"10.1016/j.hcc.2023.100193","DOIUrl":null,"url":null,"abstract":"<div><p>Mobile networks are facing unprecedented challenges due to the traits of large scale, heterogeneity, and high mobility. Fortunately, the emergence of fog computing offers surprisingly perfect solutions considering the features of consumer proximity, wide-spread geographical distribution, and elastic resource sharing. In this paper, we propose a novel mobile networking framework based on fog computing which outperforms others in resilience. Our scheme is constituted of two parts: the personalized customization mobility management (MM) and the market-driven resource management (RM). The former provides a dynamically customized MM framework for any specific mobile node to optimize the handoff performance according to its traffic and mobility traits; the latter makes room for economic tussles to find out the competitive service providers offering a high level of service quality at sound prices. Synergistically, our proposed MM and RM schemes can holistically support a full-fledged resilient mobile network, which has been practically corroborated by numerical experiments.</p></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":"4 2","pages":"Article 100193"},"PeriodicalIF":3.2000,"publicationDate":"2023-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667295223000910/pdfft?md5=14166eeafd4e4d042e4b4bbd39b389c3&pid=1-s2.0-S2667295223000910-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Fog-computing based mobility and resource management for resilient mobile networks\",\"authors\":\"Hang Zhao,&nbsp;Shengling Wang,&nbsp;Hongwei Shi\",\"doi\":\"10.1016/j.hcc.2023.100193\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Mobile networks are facing unprecedented challenges due to the traits of large scale, heterogeneity, and high mobility. Fortunately, the emergence of fog computing offers surprisingly perfect solutions considering the features of consumer proximity, wide-spread geographical distribution, and elastic resource sharing. In this paper, we propose a novel mobile networking framework based on fog computing which outperforms others in resilience. Our scheme is constituted of two parts: the personalized customization mobility management (MM) and the market-driven resource management (RM). The former provides a dynamically customized MM framework for any specific mobile node to optimize the handoff performance according to its traffic and mobility traits; the latter makes room for economic tussles to find out the competitive service providers offering a high level of service quality at sound prices. Synergistically, our proposed MM and RM schemes can holistically support a full-fledged resilient mobile network, which has been practically corroborated by numerical experiments.</p></div>\",\"PeriodicalId\":100605,\"journal\":{\"name\":\"High-Confidence Computing\",\"volume\":\"4 2\",\"pages\":\"Article 100193\"},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2023-11-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2667295223000910/pdfft?md5=14166eeafd4e4d042e4b4bbd39b389c3&pid=1-s2.0-S2667295223000910-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"High-Confidence Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2667295223000910\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"High-Confidence Computing","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2667295223000910","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0

摘要

移动网络因其大规模、异构性和高流动性等特点而面临着前所未有的挑战。幸运的是,雾计算的出现提供了令人惊喜的完美解决方案,它考虑到了消费者就近、广泛的地理分布和弹性资源共享等特点。在本文中,我们提出了一种基于雾计算的新型移动网络框架,该框架在弹性方面优于其他框架。我们的方案由两部分组成:个性化定制移动管理(MM)和市场驱动资源管理(RM)。前者为任何特定移动节点提供动态定制的移动性管理框架,以根据其流量和移动性特征优化切换性能;后者为经济角力留出空间,以找出以合理价格提供高水平服务质量的有竞争力的服务提供商。通过协同作用,我们提出的 MM 和 RM 方案可全面支持成熟的弹性移动网络,这一点已通过数值实验得到实际证实。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Fog-computing based mobility and resource management for resilient mobile networks

Mobile networks are facing unprecedented challenges due to the traits of large scale, heterogeneity, and high mobility. Fortunately, the emergence of fog computing offers surprisingly perfect solutions considering the features of consumer proximity, wide-spread geographical distribution, and elastic resource sharing. In this paper, we propose a novel mobile networking framework based on fog computing which outperforms others in resilience. Our scheme is constituted of two parts: the personalized customization mobility management (MM) and the market-driven resource management (RM). The former provides a dynamically customized MM framework for any specific mobile node to optimize the handoff performance according to its traffic and mobility traits; the latter makes room for economic tussles to find out the competitive service providers offering a high level of service quality at sound prices. Synergistically, our proposed MM and RM schemes can holistically support a full-fledged resilient mobile network, which has been practically corroborated by numerical experiments.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
4.70
自引率
0.00%
发文量
0
期刊最新文献
Erratum to “Exploring Personalized Internet of Things (PIoT), social connectivity, and Artificial Social Intelligence (ASI): A survey” [High-Confidence Computing 4 (2024) 100242] Identity-based threshold (multi) signature with private accountability for privacy-preserving blockchain Navigating the Digital Twin Network landscape: A survey on architecture, applications, privacy and security Erratum to “An effective digital audio watermarking using a deep convolutional neural network with a search location optimization algorithm for improvement in Robustness and Imperceptibility” [High-Confid. Comput. 3 (2023) 100153] A lightweight practical consensus mechanism for supply chain blockchain
×
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