Abstract

<span>Packet routing in wireless sensor network is one of the most crucial aspects as it controls the way packets move through sensor nodes with various capabilities to reach to the destination node. Inefficient routing process may lead to higher energy consumption, higher failure rate, and lower throughput. Metaheuristic algorithms have been some of the common approaches to solve these problems due to their adaptability with dynamic environment. This paper proposed a hybrid metaheuristics routing algorithm that hybridizes ant colony system and tabu search which focuses on exploitation and exploration mechanism while reducing the local optima. The proposed algorithm uses ant colony system technique to discover the best path for packet transmission by considering the energy level of each sensor node. Additionally, tabu search technique is applied to overcome the local optima problem by temporarily suspending the bad nodes and initiate backward movement with the aim to prevent the search agent from getting trapped in a blind alley. The proposed hybrid routing algorithm was evaluated against single and hybrid routing algorithms in terms of throughput, energy consumption, and energy efficiency. Experimental results showed that the proposed algorithm outperformed the other routing algorithms in terms of throughput, energy consumption, and energy efficiency.</span>

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