Bio-inspired Solution for Cluster-Tree Based Data Collection Protocol in Wireless Sensors Networks

Abstract

The effectiveness of WSNs depends on the data collection scheme since the design of an energy-efficient, long-time WSN has been a challenge for over a decade. To address this issue, we propose a Cluster-tree Data Collection Protocol using a hybrid meta-heuristic algorithm termed Hybrid Bio-Inspired Protocol (HBIP). The idea consists of integrating the Bacterial Foraging optimization (BFO) swarming step into the exploitation phase in the Artificial Bee Colony algorithm (ABC). Our solution efficiently builds clusters and elects the optimal Cluster Heads (CHs). The results of the simulation show that HBIP outperforms the traditional clustering protocol LEACH and meta-heuristics like ABC and BFO in terms of throughput, energy consumption, network lifetime, and data packets received at the BS.