Distance Reduction in Mobile Wireless Communication: Lower Bound Analysis and Practical Attainment

The transmission energy required for a wireless communication increases superlinearly with the communication distance. In a mobile wireless network, nodal movement can be exploited to greatly reduce the energy required by postponing communication until the sender moves close to a target receiver, subject to application deadline constraints. In this paper, we characterize the fundamental performance limit, namely the lower bound expected communication distance, achievable by any postponement algorithm within given deadline constraints. Our analytical results concern mainly the random waypoint (RWP) model. Specifically, we develop a tight analytical lower bound of the achievable expected communication distance under the model. In addition, we define a more general map-based movement model, and characterize its lower bound distance by simulations. We also address the practical attainment of distance reduction through movement-predicted communication. Specifically, whereas prior work has experimentally demonstrated the effectiveness a least distance (LD) algorithm, we provide an absolute performance measure of how closely LD can match the theoretical optimum. We show that LD achieves an average reduction in the expected communication distance within 62% to 94% of the optimal, over a realistic range of nodal speeds, for both the RWP and map-based models.