Greedy geographic routing algorithms in a real environment

Existing theoretical and simulation studies on georouting appear detached from experimental studies in real environments. We set up our test environment by using WSN430 wireless sensor nodes. To overcome the need for significant number of wireless nodes required to perform a realistic experiment in high density network, we introduce a novel approach emulation by using relatively small number of nodes in 1-hop experimental setup. Source node is a fixed sensor, all available sensors are candidate forwarding neighbors with virtual destination. Source node makes one forwarding step, destination position is adjusted, and the same source again searches for best forwarder. We compare three georouting algorithms. We introduce here Greedy geographical routing Algorithms in a REal environment (GARE) which builds a RNG by using ET X(uv) |uv| as edge weight (ET X(uv) counts all transmissions and possibly acknowledgments between two nodes until message is received), and selects RNG neighbor with greatest progress toward destination (if none of RNG neighbors has progress, all neighbors are considered). Our experiments show that GARE is significantly more efficient than existing XTC algorithm (applying RNG on ET X(uv)) in energy consumption. COP GARE selects neighbor with progress that minimizes ET X(uv) |uv| , and outperforms both algorithms.