The advent of multi-hop mobile ad hoc networks (MANETs) has led to a number of application scenarios consisting of autonomous mobile agents performing long term sensing and communication tasks. Energy is a key concern in designing MANETs as the nodes usually have limited battery power. As communication will undoubtedly be one of the essential functionalities of such networks, optimizing the energy consumed for data transmissions is of utmost importance. In this dissertation, we have developed a mobility prediction based framework for deploying controllable mobile relay nodes for optimizing the energy consumption in MANETs. We present two instances of the relay deployment problem, together with the solutions, to achieve different goals. Instance 1, termed Min-Total, aims to minimize the total energy consumed by the traditional nodes during data transmission, while instance 2, termed Min-Max, aims to minimize the maximum energy consumed by a traditional node during data transmission. Our solutions also enable the prioritization of individual nodes in the network based on residual energy profiles and contextual significance. In addition, we also present a mobility prediction based clustering framework to dynamically organize the network into stable sub-structures to assist in an initial deployment of the relay nodes.

We perform an extensive simulation study to evaluate the performance of the relay deployment algorithms underying network conditions. We also investigate the performance of the proposed framework under different mobility prediction schemes. Results indicate that even when the relay nodes constitute a small fraction of the total nodes in the network, the proposed framework results in significant energy savings. Further, we observed that while both the schemes have their potential advantages, the differences between the two optimization schemes is clearly highlighted in a sparse network.