Improved lifetime in wireless sensor networks based on hybrid whale and simulated annealing algorithm

Increasing the lifetime of the network is one of the major challenges in wireless sensor networks and so far several methods have been proposed in this regard, each of which has advantages and disadvantages. In this paper, a protocol based on the improved whale optimization algorithm with the simulated annealing optimization algorithm and fuzzy clustering is proposed for clustering the wireless sensor network and reducing its energy consumption. Examination of the research findings in two simulation scenarios showed that the protocol based on the improved whale optimization algorithm compared to the protocol based on the improved bee optimization algorithm delayed the average death time of the first node in the network by an average of 12% and energy consumption improved by an average of 2%.

Keywords:

Wireless Sensor Network , Clustering , Lifetime , Energy Consumption , Wall Optimization Algorithm