Physical-Assisted Routing for Proactive Avoidance of Nomadic Obstacles in IoT

Author:

Xia Ming1ORCID,Jin Jiaquan1ORCID,Liu Biqian1ORCID,Hu Yu Hen2ORCID,Wang Xiaoyan1ORCID,Chi Kaikai1ORCID

Affiliation:

1. Zhejiang University of Technology, Hangzhou, Zhejiang, China

2. University of Wisconsin-Madison

Abstract

With the broadening of the radio spectrum to higher frequency bands, wireless links are more prone to blockages by nomadic obstacles. However, existing routing schemes mostly follow the network-oriented design principle, which makes it difficult to react quickly to sudden obstruction. This article proposes PAR, a novel physical-assisted routing scheme for the Internet of Things. PAR takes a physical-oriented viewpoint attempting to mitigate unexpected link blockages by leveraging sensor observations of obstacles at individual nodes. It analyzes the signatures of sensor measurements to directly estimate the positions and sizes of obstacles and to proactively infer remedial routing decisions even before the transmission failure occurs. During the network deployment time, PAR lets each node learn and calibrate the geographic distribution of neighbors with respect to its sensor measurements by exchanging the sensor observations of a mobile guidance obstacle. During the runtime, an obstacle bypassing algorithm is then developed to find the shortest detour routes by comparing the local sensor measurements with the calibrated positions of neighbors to immediately resume data forwarding. We evaluate the efficacy of PAR using simulation and a real-world testbed. It is observed that PAR significantly improves the success rate while reducing redundant hops and routing control overhead.

Funder

National Natural Science Foundation of China

Zhejiang Provincial Research Project on the Application of Public Welfare Technologies

Zhejiang Provincial Natural Science Foundation of China for Distinguished Young Scholars

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications

Reference39 articles.

1. A reinforcement learning-based link quality estimation strategy for RPL and its impact on topology management

2. Atmel. 2010. AT86RF212 Data Sheet. Retrieved October 7 2022 from http://ww1.microchip.com/downloads/en/DeviceDoc/doc8168.pdf.

3. Radio link quality estimation in wireless sensor networks: A survey;Baccour Nouha;ACM Transactions on Sensor Networks,2012

4. Thanassis Boulis. 2018. Castalia. Retrieved October 7 2022 from https://github.com/boulis/Castalia.

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Radio Environment Map Based Routing Protocol for UAV Networks;2023 IEEE 29th International Conference on Parallel and Distributed Systems (ICPADS);2023-12-17

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