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Distributed faulty node detection and recovery scheme for wireless sensor networks using cellular learning automata

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Abstract

In a wireless sensor network (WSN), there is always the possibility of failure in sensor nodes. Quality of Service (QoS) of WSNs is highly degraded due to the faulty sensor nodes. One solution to this problem is to detect and reuse faulty sensor nodes as much as possible. Accordingly, QoS of WSNs can be improved. This paper proposes a distributed cellular learning automata faulty node classification and management scheme for WSNs that can detect and reuse faulty sensor nodes according to their fault status. The proposed method uses cellular learning automata to assign a status to each node based on hardware conditions, which makes the nodes do one of the network’s operations. The proposed algorithm is experimented extensively and the results are compared with the existing algorithms to demonstrate the effectiveness of the proposed algorithm.

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Correspondence to Ramin Yarinezhad.

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Yarinezhad, R., Hashemi, S.N. Distributed faulty node detection and recovery scheme for wireless sensor networks using cellular learning automata. Wireless Netw 25, 2901–2917 (2019). https://doi.org/10.1007/s11276-019-02005-7

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