Layout optimization for a wireless sensor network using a multi-objective genetic algorithm

This paper examines the optimization of wireless sensor network layouts. To transmit their data to the base, all the sensors are required to be connected to a high-energy communication node, which serves as a relay from the ground to a satellite or to a high-altitude aircraft. The sensors are assumed to have a fixed communication and a fixed sensing range, which can significantly vary depending on the type of sensing performed. This simple framework serves to benchmark a multi objective genetic algorithm (MOGA) for the sensor placement, where the two competing objectives considered are the total sensor coverage and the lifetime of the network. The MOGA is then used to show that, for different relative sensing ranges, two fundamentally different types of layouts are obtained: one with the sensors closely packed together, the other with the sensors organized in a hub-and-spoke manner. The ratio of sensing to communication range is shown to be the discriminating factor.