Energy Optimization under Informed Mobility

Energy optimization is important in wireless ad hoc networks, where node battery power is usually limited. Research results show that such a network can exploit controlled node mobility to reduce communication-related energy consumption. However, node movement itself usually consumes energy. In this paper we study the energy optimization problem that accounts for energy costs associated with both communication and physical node movement. We refer to this model as informed mobility. We first review the theoretical foundations on how to reduce total communication energy consumption, as well as increase system lifetime, by combining node movement and transmission power adaptation. Next, we describe and analyze the informed mobility optimization problem. Based on this analysis, we introduce localized algorithms and protocols for informed mobility. We propose iMobif, a flow-based informed mobility framework that collects network information for mobility decision making. We demonstrate how to use iMobif to minimize total communication energy consumption as well as to maximize system lifetime. We compare the performance of iMobif to that of systems with no mobility or only cost-unaware mobility. Simulation results show iMobif is effective in reducing energy consumption relative to such systems.