Lifetime Aware Resource Management for Sensor Network Using Distributed Genetic Algorithm

In this work we consider lifetime-aware resource management for sensor network using distributed genetic algorithm (GA). Our goal is to allocate different detection methods to different sensor nodes in the way such that the required detection probability can be achieved while the network lifetime is maximized. The contribution of this paper is twofold. Firstly, the resource management problem is formulated as a constraint optimization problem and is solved using a distributed GA. Secondly, empirical analysis results are provided that reveals the relationship between the configuration parameters and the quality of the search. A regression model is designed to estimate the runtime of the distributed GA given the configuration parameters. The model is utilized to find energy efficient configurations of the algorithm.