Proposing a Hybrid Topological Organization for Non-Misbehaving Nodes with Optimal Path Selection Using Game-Theoretic Approach

Kanmani S, M. Murali
{"title":"Proposing a Hybrid Topological Organization for Non-Misbehaving Nodes with Optimal Path Selection Using Game-Theoretic Approach","authors":"Kanmani S, M. Murali","doi":"10.3844/jcssp.2023.1180.1189","DOIUrl":null,"url":null,"abstract":"In dynamic communication networks, improvement of energy efficiency is one of the major challenges for reliable communication. By considering this challenge, we focus to develop the topology of the network. In this study, we design a hybrid star-mesh topology for minimizing the latency as well as energy consumption of the network. In the hybrid network topology, the Ad-Hoc On-Demand Multipath Distance Vector (AOMDV) routing protocol is used to establish multiple paths between source and destination. Among the multiple paths, the optimal path is chosen using Chimp Optimization Algorithm (ChOA) when the routing path loses its energy level. The optimal path selection leads to enhancing the energy efficiency of the network. Simulation results discuss the superior performance of the proposed scheme in terms of delivery ratio, energy consumption, delay, and throughput by 7% on aggregate.","PeriodicalId":40005,"journal":{"name":"Journal of Computer Science","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computer Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3844/jcssp.2023.1180.1189","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

In dynamic communication networks, improvement of energy efficiency is one of the major challenges for reliable communication. By considering this challenge, we focus to develop the topology of the network. In this study, we design a hybrid star-mesh topology for minimizing the latency as well as energy consumption of the network. In the hybrid network topology, the Ad-Hoc On-Demand Multipath Distance Vector (AOMDV) routing protocol is used to establish multiple paths between source and destination. Among the multiple paths, the optimal path is chosen using Chimp Optimization Algorithm (ChOA) when the routing path loses its energy level. The optimal path selection leads to enhancing the energy efficiency of the network. Simulation results discuss the superior performance of the proposed scheme in terms of delivery ratio, energy consumption, delay, and throughput by 7% on aggregate.
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
利用博弈论方法提出一种具有最优路径选择的非异常节点混合拓扑组织
在动态通信网络中,提高能源效率是实现可靠通信的主要挑战之一。考虑到这一挑战,我们专注于开发网络的拓扑结构。在本研究中,我们设计了一种混合星形网格拓扑结构,以最大限度地减少网络的延迟和能耗。在混合网络拓扑中,使用Ad-Hoc按需多路径距离矢量(AOMDV)路由协议在源和目的之间建立多条路径。在多条路径中,使用黑猩猩优化算法(Chimp Optimization Algorithm, ChOA)在路由路径丢失能级时选择最优路径。最优路径选择可以提高网络的能效。仿真结果表明,该方案在传输率、能耗、延迟和吞吐量等方面的总体性能优于传统方案。
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
Journal of Computer Science
Journal of Computer Science Computer Science-Computer Networks and Communications
CiteScore
1.70
自引率
0.00%
发文量
92
期刊介绍: Journal of Computer Science is aimed to publish research articles on theoretical foundations of information and computation, and of practical techniques for their implementation and application in computer systems. JCS updated twelve times a year and is a peer reviewed journal covers the latest and most compelling research of the time.
期刊最新文献
Features of the Security System Development of a Computer Telecommunication Network Performance Assessment of CPU Scheduling Algorithms: A Scenario-Based Approach with FCFS, RR, and SJF Website-Based Educational Application to Help MSMEs in Indonesia Develop A Multi-Split Cross-Strategy for Enhancing Machine Learning Algorithms Prediction Results with Data Generated by Conditional Generative Adversarial Network Improving the Detection of Mask-Wearing Mistakes by Deep Learning
×
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