Optimum communication paths for mobile WSNs using genetic algorithms

Efficient energy consumption through optimum communication paths is a key element in extending the lifetime of wireless sensor networks. In this paper we propose a genetic algorithm based path optimization method for mobile wireless sensor networks with nodes that travel on random paths with different speeds. A detailed description of the algorithm stages and how they were implemented is presented as well as the MATLAB based simulation that was developed and used to determine the performance of the proposed algorithm. Using the multi-objective function of the genetic algorithm the optimization criterion can be adjusted to consider either shortest path, minimum number of hops or a combination of the two. Results show that the genetic algorithm can be successfully used to determine real time optimum communication paths between sensor nodes and they also show that the criterion for electing these paths is in tight relationship with the network topology and movement of nodes.