Brief announcement: locality-based aggregate computation in wireless sensor networks

We present DRR-gossip, an energy-efficient and robust aggregate computation algorithm in sensor networks. We prove that the DRR-gossip algorithm requires <b>O</b>(<b>n</b>) messages and <b>O</b>(<i>n</i>^3/2/log^1/2 <i>n</i>) one-hop wireless transmissions to obtain aggregates on a random geometric graph. This reduces the energy consumption by at least a factor of 1/log <i>n</i> over the standard uniform gossip algorithm. Experiments validate the theoretical results and show that DRR-gossip needs much less transmissions than other gossip-based schemes.