Energy efficient networking via dynamic relay node selection in wireless networks

Mobile wireless ad-hoc networks need to maximize their network lifetime (defined as the time until the first node runs out of energy). In the broadcast network lifetime problem, all nodes are sending broadcast traffic, and one asks for an assignment of transmit powers to nodes, and for sets of relay nodes so that the network lifetime is maximized. The selection of a dynamic relay set consisting of a single node (the `master'), can be regarded as a special case, providing lower bounds to the optimal lifetime in the general setting. This paper provides a preliminary analysis of such a `dynamic master selection' algorithm, comparing relaying to direct routing

Energy-aware routing algorithms for wireless ad hoc networks with heterogeneous power supplies

Although many energy-aware routing schemes have been proposed for wireless ad hoc networks, they are not optimized for networks with heterogeneous power supplies, where nodes may run on battery or be connected to the mains (grid network). In this paper, we propose several energy-aware routing algorithms for such ad hoc networks. The proposed algorithms feature directing the traffic load dynamically towards mains-powered devices keeping the hop count of selected routes minimal. We unify these algorithms into a framework in which the route selection is formulated as a bi-criteria decision making problem. Minimizing the energy cost for end-to-end packet transfer and minimizing the hop count are the two criteria in this framework. Various algorithms that we propose differ in the way they define the energy cost for end-to-end packet traversal or the way they solve the bi-criteria decision making problem. Some of them consider the energy consumed to transmit and receive packets, while others also consider the residual battery energy of battery-enabled nodes. The proposed algorithms use either the weighted sum approach or the lexicographic method to solve the bi-criteria decision making problem. We evaluate the performance of our algorithms in static and mobile ad hoc networks, and in networks with and without transmission power control. Through extensive simulations we show that our algorithms can significantly enhance the lifetime of battery-powered nodes while the hop count is kept close to its optimal value. We also discuss the scenarios and conditions in which each algorithm could be suitably deployed

Energy aware routing protocols in ad hoc wireless networks

In Mobile Ad hoc Network, communication at mobile nodes can be achieved by using multi-hop wireless links. The architecture of such a network is based, not on a centralized base station but on each node acting as a router to forward data packets to other nodes in the network. The aim of each protocol, in an ad hoc network, is to find valid routes between two communicating nodes. These protocols must be able to handle high mobility of the nodes which often cause changes in the network topology. Every ad hoc network protocol uses some form of a routing algorithm to transmit between nodes based on a mechanism that forwards packets from one node to another in the network. These algorithms have their own way of finding a new route or modifying an existing one when there are changes in the network. The novel area of this research is a proposed routing algorithm which improves routing and limits redundant packet forwarding, especially in dense networks. It reduces the routing messages and consequently power consumption, which increases the average remaining power and the lifetime of the network. The first aim of this research was to evaluate various routing algorithms in terms of power. The next step was to modify an existing ad hoc routing protocol in order to improve the power consumption. This resulted in the implementation of a dynamic probabilistic algorithm in the route request mechanism of an ad hoc On-Demand Distance Vector protocol which led to a 3.0% improvement in energy consumption. A further extension of the approach using Bayesian theory led to 3.3% improvement in terms of energy consumption as a consequence of a reduction in MAC Load for all network sizes, up to 100 nodes.EThOS - Electronic Theses Online ServiceGBUnited Kingdo