Grey Wolf Optimization-Based Energy-Efficient Routing Protocol for Heterogeneous Wireless Sensor Networks

A three-level hybrid clustering routing protocol algorithm (MLHP) based on the Grey Wolf Optimizer (GWO) for wireless sensor networks is proposed in this paper. A centralized selection is proposed for Level One, in which the base station (BS) plays a great role in selecting cluster heads. In Level Two, a GWO routing for data transfer is proposed, were nodes select the best route to the BS to save more energy. And, a distributed clustering based on a cost function is proposed for Level Three. The algorithm was evaluated through tests of a network's energy efficiency, lifetime, and stability period. Comparisons were made with the best-known routing protocols to measure the performance of the proposed algorithm. The results showed improved performance of the proposed algorithm in terms of longer network lifetime, longer stability period, and more residual energy when compared with the other algorithms.