Energy consumption is one of the most serious issues in designing Wireless Sensor Networks (WSNs) for maximizing its lifetime and stability. Clustering is considered as one of the topology control methods for maintaining the stability of WSNs which can significantly reduce energy consumption in WSNs. However, using different methods for the selection of cluster head is an important challenge in this domain of research. Load balanced clustering is known as an NP-hard problem for a WSN along with unequal load for sensor nodes. The Imperialist Competitive Algorithm (ICA) is regarded as an evolutionary method which can be used for finding a quick and efficient solution to such problems. In this paper, a clustering method with an evolutionary approach is introduced which investigates the issues of load balance and energy consumption of WSNs in the equal and unequal load modes so as to select optimal cluster heads. Simulation of the proposed method, carried out via NS2, indicated that it improves the criteria of energy consumption, the number of active sensor nodes and execution time.
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Dehestani, F., Jabraeil Jamali, M.A. Load Balanced Clustering Based on Imperialist Competitive Algorithm in Wireless Sensor Networks. Wireless Pers Commun (2020) doi:10.1007/s11277-020-07030-w
- Wireless sensor network
- Clustering algorithm
- Imperialist competitive algorithm
- Load balancing