DocumentCode :
19702
Title :
Link Scanner: Faulty Link Detection for Wireless Sensor Networks
Author :
Qiang Ma ; Kebin Liu ; Zhichao Cao ; Tong Zhu ; Yunhao Liu
Author_Institution :
Sch. of Software, Tsinghua Univ., Beijing, China
Volume :
14
Issue :
8
fYear :
2015
fDate :
Aug. 2015
Firstpage :
4428
Lastpage :
4438
Abstract :
In large-scale wireless sensor networks, faulty link detection plays a critical role in network diagnosis and management. Most potential network bottlenecks such as network partition and routing errors can be detected by link scan. Since sequentially checking all potential links incurs high transmission and storage cost, we propose a passive scheme Link Scanner (LS) for monitoring wireless links. As we know, to maintain a sensor network running in a normal condition, many applications in flooding manner are necessary, such as time synchronization, reprogramming, protocol update, etc. During such regular flooding processes that for other purposes originally, LS passively collects hop counts of received probe messages at sensor nodes. Based on the observation that faulty links can result in mismatch between received hop counts and network topology, LS deduces all links´ status with a probabilistic model. We evaluate our scheme by carrying out experiments on a testbed with 60 TelosB motes and conducting extensive simulation tests. A real outdoor system is also deployed to verify that LS can be reliably applied to surveillance networks.
Keywords :
probability; wireless sensor networks; faulty link detection; hop counts; large-scale wireless sensor networks; link scanner; network diagnosis; network management; network topology; probabilistic model; regular flooding process; surveillance networks; wireless links; Monitoring; Network topology; Probes; Routing; Topology; Wireless communication; Wireless sensor networks; Wireless sensor networks; link detection; network diagnosis; network diagnosis.;
fLanguage :
English
Journal_Title :
Wireless Communications, IEEE Transactions on
Publisher :
ieee
ISSN :
1536-1276
Type :
jour
DOI :
10.1109/TWC.2015.2421353
Filename :
7081755
Link To Document :
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