Tošić, Tamara; Thomos, Nikolaos; Frossard, Pascal (2013). Distributed sensor failure detection in sensor networks. Signal Processing, 93(2), 399 - 410. Elsevier 10.1016/j.sigpro.2012.07.028
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We investigate the problem of distributed sensors' failure detection in networks with a small number of defective sensors, whose measurements differ significantly from the neighbor measurements. We build on the sparse nature of the binary sensor failure signals to propose a novel distributed detection algorithm based on gossip mechanisms and on Group Testing (GT), where the latter has been used so far in centralized detection problems. The new distributed GT algorithm estimates the set of scattered defective sensors with a low complexity distance decoder from a small number of linearly independent binary messages exchanged by the sensors. We first consider networks with one defective sensor and determine the minimal number of linearly independent messages needed for its detection with high probability. We then extend our study to the multiple defective sensors detection by modifying appropriately the message exchange protocol and the decoding procedure. We show that, for small and medium sized networks, the number of messages required for successful detection is actually smaller than the minimal number computed theoretically. Finally, simulations demonstrate that the proposed method outperforms methods based on random walks in terms of both detection performance and convergence rate.
|Item Type:||Journal Article (Original Article)|
|Division/Institute:||08 Faculty of Science > Institute of Computer Science (INF) > Communication and Distributed Systems (CDS)
08 Faculty of Science > Institute of Computer Science (INF)
|UniBE Contributor:||Thomos, Nikolaos|
|Subjects:||000 Computer science, knowledge & systems
500 Science > 510 Mathematics
|Submitter:||Jonnahtan Eduardo Saltarin de Arco|
|Date Deposited:||12 Mar 2014 13:51|
|Last Modified:||05 Oct 2015 09:13|
|Uncontrolled Keywords:||Distributed algorithms; Detection; Group Testing; Sensor networks|