Abstract
The main purpose of localization in wireless sensor networks is to determine the location of the randomly collected sensors. Recently, bio-inspired localization techniques have become popular thanks to its precise and fast solution. In this paper, a recently developed meta-heuristic algorithm based on the social behavior of chickens called chicken swarm optimization (CSO) is used to solve the node localization problem. The studies that we have carried out have demonstrated the clear effect of our proposed approach by changing the characteristics of the network and the number of chickens used, as well as its ability to improve a classical approach based on CSO; and the comparison results with PSO showing the superiority of proposed approach.
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