Title
EasyGo: Low-cost and robust geographic opportunistic sensing routing in a strip topology wireless sensor network.
Abstract
With the fast increasing popularity of smart device communication technologies, the wireless networks on mobile sensing applications have received much attention. Wireless Sensor Networks (WSNs) with a strip structure are ubiquitous in real world deployments, such as pipeline monitoring, water quality monitoring as well as Great Wall monitoring. However, the existing routing methods will select the next-hop node that deviates from the transmission direction to sink node in strip networks with high curvature, leading to the high communication failure rate and energy consumption. To this end, we propose a new geographic routing sensing opportunistic approach, named EasyGo, to cope with the routing problem, i.e., the transmission success rate decreases in the complicated strip networks. Specifically, by investigating the transmission direction, we propose a new candidate selection algorithm SLS, which introduces the concepts of layer slicing and virtual sinks to improve the transmission success rate in strip WSNs. Theoretical analysis and extensive simulations illustrate the high efficiency and transmission performance of the proposed EasyGo strategy for strip WSNs. Furthermore, we implement the EasyGo on the testbed with Z-Stack™ nodes. Compared with the classic algorithms, our EasyGo improves the transmission success rate by up to 10%, reduces the communication overhead and the energy consumption rate by up to 11.8% and 5%, respectively.
Year
DOI
Venue
2018
10.1016/j.comnet.2018.07.002
Computer Networks
Keywords
Field
DocType
Wireless sensor networks,Routing algorithms,Strip network monitoring
Wireless network,Smart device,Computer science,Selection algorithm,Testbed,Computer network,Failure rate,Wireless sensor network,Geographic routing,Energy consumption,Distributed computing
Journal
Volume
ISSN
Citations 
143
1389-1286
1
PageRank 
References 
Authors
0.34
29
10
Name
Order
Citations
PageRank
Chen Liu14711.48
Dingyi Fang225252.62
yue hu3362.36
Shensheng Tang428926.45
Dan Xu5166.37
Wen Cui610.34
Xiaojiang Chen715736.57
Baoying Liu813.72
Guangquan Xu917133.20
Hao Chen1011.02