Towards an Improved Energy Efficient and End-to-End Secure Protocol for IoT Healthcare Applications

Author:

Ahmad Arshad12ORCID,Ullah Ayaz2,Feng Chong1ORCID,Khan Muzammil3ORCID,Ashraf Shahzad4,Adnan Muhammad5,Nazir Shah2ORCID,Khan Habib Ullah6ORCID

Affiliation:

1. School of Computer Science & Technology, Beijing Institute of Technology, Beijing, China

2. Department of Computer Science, University of Swabi, Anbar, Pakistan

3. Department of Computer Science, University of Swat, Swat, Pakistan

4. College of Internet of Things Engineering, Hohai University, Changzhou, Jiangsu, China

5. Department of Computer Science, Abdul Wali Khan University, Mardan, Pakistan

6. Department of Accounting & Information Systems, Qatar University, Doha, Qatar

Abstract

In this paper, we proposed LCX-MAC (local coordination X-MAC) as an extension of X-MAC. X-MAC is an asynchronous duty cycle medium access control (MAC) protocol. X-MAC used one important technique of short preamble which is to allow sender nodes to quickly send their actual data when the corresponding receivers wake up. X-MAC node keeps sending short preamble to wake up its receiver node, which causes energy, increases transmission delay, and makes the channel busy since a lot of short preambles are discarded, as these days Internet of Things (IoT) healthcare with different sensor nodes for the healthcare is time-critical applications and needs a quick response. A possible improvement over X-MAC is that local information of each node will share with its neighbour node. This local information exchanged will cause much less overhead than in the nodes which are synchronized. To calculate the effect of this the local coordination on X-MAC in this paper, we built an analytical model of LCX-MAC that incorporates the local coordination in X-MAC. The analytical results show that LCX-MAC outperformed X-MAC and X-MAC/BEB in terms of throughput, delay, and energy.

Funder

National Natural Science Foundation of China

Publisher

Hindawi Limited

Subject

Computer Networks and Communications,Information Systems

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3