Routing for multi -hop wireless networks

Over the last few years, multi-hop wireless networks have received considerable attention. Routing is an important functionality for such networks as it is closely tied to energy efficiency, scalability, and performance. Unlike wired networks, in wireless systems due to the nature of the communication environment, issues such as mutual interference and errors need to be accounted for in the overall design. In Part I, we develop an energy-efficient routing algorithm that considers intrinsic wireless network characteristics to maximize network performance. To that end, we explicitly study the impact of interference on the network, and combine three key wireless metrics: transmission power; interference ; and residual energy. The proposed algorithm is designed to accommodate any combination of these key elements and to automatically detour around congested areas, which helps improve overall network performance. Using simulations, we show that the routes chosen by our algorithm (centralized and distributed) are more energy efficient than the-state-of-the-art. In Part II, we study geographic information issues on routing for multi-hop wireless networks: routing algorithm design and performance analysis. Due to the simplicity and scalability, routing algorithms using geographic information (geographic routing) have been proposed. However, in practice location errors could significant degrade routing performance. In the mobile environment, the performance degradation becomes even more severe. Hence, we study the impact of location errors on geographic routing algorithms and propose a routing algorithm to mitigate the impact of location errors. Geographic and geometric attributes affect network performance. We use geometric probability to analyze the nodal load, which is defined as the number of packets served at a node, induced by straight line routing in large homogeneous multi-hop wireless networks. Our analysis shows that the nodal load at each node is a function of the node\u27s Voronoi cell, the node\u27s location in the network, and the traffic pattern specified by the source and destination randomness and straight line routing. Since load distribution depends on the traffic pattern generated by straight line routing, contrary to conventional wisdom, straight line routing can balance the load over the network, depending on the traffic patterns