A Review of and a Proposal for Cross-Layer Design for Efficient Routing and Secure Data Aggregation over WSN

Mukesh Mishra, G. S. Gupta, X. Gui
{"title":"A Review of and a Proposal for Cross-Layer Design for Efficient Routing and Secure Data Aggregation over WSN","authors":"Mukesh Mishra, G. S. Gupta, X. Gui","doi":"10.1109/CINE.2017.30","DOIUrl":null,"url":null,"abstract":"Sensors these days are ubiquitous. They are in homes, factories, farms and just about everywhere. For distributed sensing requirements, several sensors are deployed and connected on a wireless media forming a Wireless Sensor Network (WSN). Sensor nodes communicate with each other and with a base station (BS). In this paper we first review recent work which is focused on cross-layer WSN design techniques based on the Open System Interconnection (OSI) model. Sensor nodes are often clustered and cluster heads (CH) are used to route data to the BS. We have also reviewed constraints-based routing algorithms which select a routing path satisfying administrative-oriented or Quality of Service-oriented (QoS-oriented) constraints. The algorithms minimize costs, balance network load, or increase security. Previous works of cross-layer design for malicious node identification, diagonal data aggregation and route adjustments were deficient to support WSN. The major problem was higher energy consumption and congestion during data aggregation. To overcome all the limitations and the problems that exist in cross layer design of WSN, we have proposed a novel design in this paper.","PeriodicalId":236972,"journal":{"name":"2017 3rd International Conference on Computational Intelligence and Networks (CINE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 3rd International Conference on Computational Intelligence and Networks (CINE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CINE.2017.30","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

Sensors these days are ubiquitous. They are in homes, factories, farms and just about everywhere. For distributed sensing requirements, several sensors are deployed and connected on a wireless media forming a Wireless Sensor Network (WSN). Sensor nodes communicate with each other and with a base station (BS). In this paper we first review recent work which is focused on cross-layer WSN design techniques based on the Open System Interconnection (OSI) model. Sensor nodes are often clustered and cluster heads (CH) are used to route data to the BS. We have also reviewed constraints-based routing algorithms which select a routing path satisfying administrative-oriented or Quality of Service-oriented (QoS-oriented) constraints. The algorithms minimize costs, balance network load, or increase security. Previous works of cross-layer design for malicious node identification, diagonal data aggregation and route adjustments were deficient to support WSN. The major problem was higher energy consumption and congestion during data aggregation. To overcome all the limitations and the problems that exist in cross layer design of WSN, we have proposed a novel design in this paper.
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
无线传感器网络中高效路由和安全数据聚合的跨层设计综述与建议
如今,传感器无处不在。它们存在于家庭、工厂、农场和几乎任何地方。为了满足分布式传感需求,将多个传感器部署并连接在无线介质上,形成无线传感器网络(WSN)。传感器节点之间相互通信,并与基站(BS)通信。本文首先回顾了基于开放系统互连(OSI)模型的无线传感器网络跨层设计技术的研究进展。传感器节点通常是聚类的,簇头(CH)用于将数据路由到BS。我们还回顾了基于约束的路由算法,它选择满足面向管理或面向服务的质量(qos)约束的路由路径。这些算法可以最大限度地降低成本,平衡网络负载或提高安全性。以往针对恶意节点识别、对角数据聚合、路由调整等跨层设计的工作缺乏对WSN的支持。主要的问题是数据聚合过程中较高的能耗和拥塞。为了克服无线传感器网络跨层设计存在的局限性和问题,本文提出了一种新的设计方案。
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
自引率
0.00%
发文量
0
期刊最新文献
Building Occupancy Detection Using Feed Forward Back-Propagation Neural Networks Stock Prediction Using Functional Link Artificial Neural Network (FLANN) Symmetric Axis Based Off-Line Odia Handwritten Character and Numeral Recognition Artificial Intelligence Techniques Used to Detect Object and Face in an Image: A Review Application of JAYA Algorithm to Tune Fuzzy-PIDF Controller for Automatic Generation Control
×
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