Abstract

Wireless Sensor Networks (WSNs) are networks of autonomous nodes used for monitoring an environment. In designing WSNs, one of the main issues is limited energy source for each sensor node. Hence, offering ways to optimize energy consumption in WSNs which eventually increases the network lifetime is strongly felt. Gravitational Search Algorithm (GSA) is a novel stochastic population-based meta-heuristic that has been successfully designed for solving continuous optimization problems. GSA has a flexible and well-balanced mechanism to enhance intensification (intensively explore areas of the search space with high quality solutions) and diversification (move to unexplored areas of the search space when necessary) abilities. In this paper, we will propose a GSA-based method for near-optimal positioning of Base Station (BS) in heterogeneous two-tiered WSNs, where Application Nodes (ANs) may own different data transmission rates, initial energies and parameter values. Here, we treat with the problem of positioning of BS in heterogeneous two-tiered WSNs as a continuous optimization problem and show that proposed GSA can locates the BS node in an appropriate near-optimal ∗Corresponding Author Received 20 July 2013; Accepted 11 June 2014 c ©2015 Academic Center for Education, Culture and Research TMU

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