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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. We consider a realistic map based stochastic movement model, of which the well known random waypoint model is a special case. For the random waypoint model, we develop a tight analytical lower bound of the achievable expected communication distance. For the general map-based model, we characterize the lower bound distance experimentally. We also address the practical attainment of distance reduction (and hence, energy savings) through movement predicted communication. Specifically, whereas prior work has presented a least distance (LD) postponement algorithm and established its effectiveness experimentally, 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 map based and random waypoint models. Moreover, the algorithm's absolute performance increases as the nodal speed or the allowable postponement delay increases.