Border Surveillance With WSN Systems in a Distributed Manner

Border surveillance is an application of wireless sensor networks (WSNs) and it is mainly used for security purpose. The present issue of implementing this application is a barrier coverage in WSNs. Due to energy constraints, minimizing energy consumption of sensors is a critical challenge. This paper presents a new distributed approach to the border surveillance in WSNs in order to maximize the number of barriers and minimize energy consumption. We use a learning automata scheme in our approach to solve this problem. We present distributed border surveillance (DBS) algorithm that aims to find the minimum possible number of nodes in each barrier to monitor the network borders. In DBS approach, learning automaton assists to find the best nodes to assure barrier coverage at any moment. The algorithm was implemented through computer simulations and compared to the existing competing algorithms. The simulation results show that the DBS scheme outperformed some state-of-art barrier-coverage algorithms.

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