Abstract

A number of energy-aware routing protocols were proposed to seek the energy efficiency of routes in multihop wireless networks. Among them, several geographical localized routing protocols were proposed to help making smarter routing decision using only local information and reduce the routing overhead. However, all proposed localized routing methods cannot guarantee the energy efficiency of their routes. In this paper, we first give a simple localized routing algorithm, called Localized Energy-Aware Restricted Neighborhood routing (LEARN), which can guarantee the energy efficiency of its route if it can find the route successfully. We then theoretically study its critical transmission radius in random networks which can guarantee that LEARN routing finds a route for any source and destination pairs asymptotically almost surely. We also extend the proposed routing into three-dimensional (3D) networks and derive its critical transmission radius in 3D random networks. Simulation results confirm our theoretical analysis of LEARN routing and demonstrate its energy efficiency in large scale random networks.

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