A Self-Organizing Heuristic for Building Optimal Heterogeneous Ad-Hoc Sensor Networks

Much of the research in the area of sensor networks is focused on homogeneous networks. Of late, there has been a steadily increasing amount of work on heterogeneous networks, mainly due to their flexibility and better fit into potential applications. In this paper, we present a heuristic, developed using a reverse engineering approach, that can be used to build efficient heterogeneous ad-hoc sensor networks based on a generic network model. A genetic algorithm is used to generate a set of heterogeneous sensor networks optimized for short paths and congestion. A thorough analysis of the optimal network set is done to extract rules and a heuristic is developed to embody these rules. The heuristic is then used to produce high-performance networks without genetic algorithms. We present simulation results and analysis of the heuristic networks and compare their performance with optimal heterogeneous networks as well as homogeneous networks