Mobile agent based moving target methods in wireless sensor networks

Wireless sensor network consists of vast low-cost nodes whose power and ability are limited. In a wireless sensor network for monitoring moving targets, the real-time optimal combination of nodes can minimize the power consumption of the entire network and the cooperation of nodes can overcome the poor ability of a single node. In this paper, a mobile agent based strategy is proposed which dynamically optimizes the combination of nodes and deploys the tasks among nodes. A method combining genetic algorithm (GA) and Hopfield neural network (HNN), called HNN-GA, is engaged to select the lowest-power-consumption combination. The nodes are divided into several computational regions according to the principle of balancing abilities and power consumption. Gradual optimization is applied to deploy the tasks and minimize the total time. The experiment results indicate the mobile agent based strategy can save energy and boost the efficiency of computations.