Memetic and Evolutionary Design of Wireless Sensor Networks Based on Complex Network Characteristics

Abstract

This work proposes the design of wireless sensor networks using evolutionary algorithms based on complex network measures. In this paper, the authors develop heuristic approaches based on genetic and memetic algorithms for finding a network configuration based on two complex network measures, the average shortest path length, and the cluster coefficient. The work begins with the mathematical model of the hub allocation problem, developed to determine the nodes that will be configured as hubs. This model was adopted within the basic and the hybrid genetic algorithm, and results reveal that the methodology allows the configuration of networks with more than a hundred nodes where some complex network measures are observed in the physical communication layer. The energy consumption and the delay could be reduced when a tree based routing is built over this physical layer.