A Pareto optimization-based approach to clustering and routing in Wireless Sensor Networks

Abstract

Clustering and routing in WSNs are two well-known optimization problems that are classified as Non-deterministic Polynomial (NP)-hard. In this paper, we propose a single multi-objective problem formulation tackling these two problems simultaneously with the aim of finding the optimal network configuration. The proposed formulation takes into consideration the number of Cluster Heads (CHs), the number of clustered nodes, the link quality between the Cluster Members (CMs) and CHs and the link quality of the constructed routing tree. To select the best multi-objective optimization method, the formulated problem is solved by two state-of-the-art Multi-Objective Evolutionary Algorithms (MOEAs), and their performance is compared using two well-known quality indicators: the hypervolume indicator and the Epsilon indicator. Based on the proposed problem formulation and the best multi-objective optimization method, we also propose an energy efficient, reliable and scalable routing protocol. The proposed protocol is developed and tested under a realistic communication model and a realistic energy consumption model that is based on the characteristics of the Chipcon CC2420 radio transceiver data sheet. Simulation results show that the proposed protocol outperforms the other competent protocols in terms of the average consumed energy per node, number of clustered nodes, the throughput at the BS and execution time.