An improved energy‐low clustering hierarchy protocol based on ensemble algorithm

Abstract

SummaryLEACH (low‐energy adaptive clustering hierarchy) protocol is an important part of wireless sensor network (WSN) and consisting of a good deal of energy‐constrained nodes. LEACH is widely used but also faces various challenges and constraints. The biggest constraint is that the energy is limited and the network life is finite. In the article, an improved ensemble algorithm based on energy‐efficient LEACH is proposed. The ensemble algorithm benefits from the cuckoo search algorithm (CS), glowworm swarm optimization (GSO), and bacterial foraging optimization (BFO). The paper enhances local and global search capabilities by modify the CS GSO and BFO algorithm. To verify results, this paper performs statistical comparatives with oriented cuckoo search (OCS), bat algorithm with characteristics of Levy flights, particle swarm optimization, and adaptive differential evolution algorithm. Comparison results shows that the new method is effective. Moreover, the research also showed the universal applicability of the ensemble strategy in solving diverse problems by using above different optimization algorithms. To further exploit our mind, this paper applies the improved coupling algorithm to LEACH for selecting the cluster‐head node. Computational experiments illustrate that the method proposed in this paper can provide very competitive results compared to these bio‐inspired LEACH, both in terms of reducing the network energy consumption and improving the lifecycle of nodes.