A mobile fault detection algorithm in heterogeneous wireless sensor networks: a bio-inspired approach
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Indian Academy of Sciences Sadhana(0123456789().,-volV)FT3 ](0123456789().,-volV)
A mobile fault detection algorithm in heterogeneous wireless sensor networks: a bio-inspired approach SERCAN YALC ¸ IN and EBUBEKIR ERDEM* Department of Computer Engineering, Firat University, 23100 Elazig, Turkey e-mail: [email protected]; [email protected] MS received 2 April 2019; revised 1 November 2019; accepted 4 November 2019 Abstract. This paper puts forth a novel mobile fault detection algorithm for wireless sensor networks (WSNs) based on bacterial-inspired optimization. We introduce a bio-swarm intelligence approach to mobile fault detection in WSNs by using voltage values. At certain times, the sensor nodes in the clustered network send data packets containing health-fitness information to cluster heads (CHs) selected by the proposed CH selection algorithm. A mobile sink (MS) collects the health status via data from all the nodes as they reach the intersection point of the CHs. After this stage, the data packets are analyzed by the MS, and hardware or software faults are detected by assessing the fitness values of the nodes. The faulty nodes are eventually discarded from the network, and recovery of the rest of the nodes in the network is satisfied. Inspired by the interaction of bacteria for feed collection, their response to chemicals, and their interaction and communication with one another, we bring an innovative approach to finding node failures or software faults in WSNs, and these failures are removed from the network to help its operation and to take measures to maintain the electrical structures. In fact, we adapt our algorithm to low energy harvesting electrical components as an example. We compare our novel algorithm with existing studies through extensive simulations in NS 2 environment based on fault detection accuracy, false alarm rate, and false positive rate criteria versus fault probability, number of nodes, and sink speed. Considering detection accuracy, the simulation results validate that our algorithm shows better performance as compared with others. Keywords. Bio-swarm optimization; mobile fault detection; mobile sink; bacterial fitness interaction; wireless sensor networks (WSNs).
1. Introduction Wireless sensor networks (WSNs) continue to be the subject of research due to their potential and unique application in areas such as environmental monitoring, health control and intelligent management, industrial performance measurement, vehicle detection and intelligent transportation systems, and weather forecasting [1–3]. A WSN consists of sensor nodes, which are composed of various small electronic units with limited battery life that, and their work is to evaluate the data obtained through intelligent measurements under certain conditions. The nodes are distributed in sensor networks according to various deployment methods; after the nodes are deployed to the network infrastructure, network connections are provided in a self-organized manner [4–6]. WSNs are plagued with lots of faults such as h
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