On the effectiveness of movement prediction to reduce energy consumption in wireless communication

Node movement can be exploited to reduce the energy consumption of wireless network communication. The strategy consists in delaying communication until a mobile node moves close to its target peer node within an application- imposed deadline. We evaluate the performance of various heuristics that, based on the movement history of the mobile node, estimate an optimal time (in the sense of least energy use) of communication subject to the delay constraint. We evaluate the impact of the node movement model, length of movement history maintained, allowable delay, single hop versus multiple hop communication, and size of data transfer on the energy consumption. We also present measurement results on an iPAQ pocket PC that quantity energy consumption in executing the prediction algorithms. Our results show that, with relatively simple and, hence, efficient prediction heuristics, energy savings in communication can significantly outweigh the energy expenses in executing the prediction algorithms. Moreover, it is possible to achieve robust system performance across diverse node movement models.