Mobile agent migration modeling and design for target tracking in wireless sensor networks

Computing paradigms play an important and fundamental role in collaborative processing in wireless sensor networks. The client/server based paradigm and the mobile agent based paradigm are two popular computing models used to facilitate collaboration among sensor nodes. In this paper, we study the key problem of determining the mobile agent itinerary for collaborative processing and model the dynamic mobile agent planning problem. We then present three itinerary planning algorithms, the static, the dynamic, and the predictive dynamic approaches to solve the target tracking problem in wireless sensor networks. We design three metrics (energy consumption, network lifetime, and the number of hops) and use simulation tools to quantitatively measure the performance of different itinerary planning algorithms. Simulation results show considerable improvement over the static itinerary and the dynamic itinerary approaches using the predictive dynamic itinerary algorithm.