An energy-efficient cluster formation in wireless sensor network using grey wolf optimisation

With the emerging technology, wireless sensor network (WSNs) plays a vital role in monitoring day-to-day life activities which suffers from various issues such as routing, intrusion, and topology control. However, to address these issues an energy-efficient cluster formation is quite important. Thus, the successive cluster formation improves the lifetime of the networks to reduce routing overheads. Our contribution in this work includes selecting energy-efficient cluster heads with the aid of the Grey Wolf Optimisation (GWO) algorithm. This algorithm attracts several researchers with its efficient leadership capability and hunting methodology but it lags in exploration and exploitation which leads to poor clustering in WSN when it is applied. The proposed methodology includes a tuning parameter for efficient exploration and exploitation later used to solve the issue which resides in WSN. The experimental results show that the proposed algorithm provides better results over cluster head selection and minimised energy consumption in WSN.