Model-based Tracking for Mobile Ad Hoc Networks

Abstract

We consider the problem of tracking of a mobile target node in a mobile ad hoc network
(MANET) set-up. We propose a lightweight probabilisticmodel-based tracking protocol (PMBT)
that achieves a short catching path with a high success rate. PMBT is a probabilistic online tracking algorithm that computes information utilities at each step, and then chooses the next step toward the target based on the maximum expected utility. Our algorithm avoids the need to maintain a tracking data structure (such as a hierarchical directory look-up structure) and the need to send periodic update messages about the target’s location.

Simulation results show, by taking a hybrid approach that integrates a gradient model and a Markov model, our algorithm significantly outperforms both gradient-based and Markov approaches alone.