Nodes localization in a wireless sensor network (WSN) aims for calculating the coordinates of unknown nodes with the assist of\nknown nodes. The performance of a WSN can be greatly affected by the localization accuracy. In this paper, a node localization\nscheme is proposed based on a recent bioinspired algorithm called Salp Swarm Algorithm (SSA). The proposed algorithm is\ncompared to well-known optimization algorithms, namely, particle swarm optimization (PSO), Butterfly optimization algorithm\n(BOA), firefly algorithm (FA), and grey wolf optimizer (GWO) under different WSN deployments. The simulation results show\nthat the proposed localization algorithm is better than the other algorithms in terms of mean localization error, computing time,\nand the number of localized nodes.
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