Energy-efficient protocols for wireless ad hoc networks

Wireless ad hoc networks have some advantages over traditional cellular type wireless networks. They are often considered when rapid deployment or reliability is important. The performance of a wireless ad hoc network is limited by its dependence on limited energy resources. In this dissertation, we attempt to improve energy efficiency by introducing energy awareness into several layers of the protocol stack. The autonomous nature of the nodes dictates that the protocols must be fully distributed.; We begin by addressing the problem of energy-efficient routing and multicasting protocols. We describe some position-based routing algorithms where directional antennas can be employed. We study the influence of the battery recovery effect and mobility on the network throughput during a network lifetime. We also present an algorithm that exploits the broadcast nature of the wireless communication environment to improve end-to-end bit error performance for a Rayleigh fading channel. For multicasting, we develop an approach that makes use of directional antennas. A model to study the performance improvement by using directional antennas is developed. A simple distributed algorithm for multicast tree construction is also proposed.; Power control is an important method to reduce interference and improve energy efficiency in wireless networks. We address the problem of joint scheduling and power control for networks supporting multicast traffic. The goal is to max imize the number of simultaneous transmissions and then to minimize the total transmit power. We propose two different approaches to address the issue.; We also propose a distributed fair scheduling framework. Unlike previous works, which assume error-free or predictable channels, our work is based on the SINR model and views channel errors as a result of the interference among the scheduled flows. We show by analysis that under the presented framework long term fairness is guaranteed; furthermore, when combined with a distributed joint scheduling and power control algorithm, the framework enables us to maximize throughput and minimize transmit power in a distributed manner.