A Probabilistic Forwarding Protocol for Efficient Data Propagation in Sensor Networks

We study the problem of data propagation in sensor networks, comprised of a large number of very small and low-cost nodes, capable of sensing, communicating and computing. The distributed co-operation of such nodes may lead to the accomplishment of large sensing tasks, having useful applications in practice. We present a new protocol for data propagation that avoids flooding by probabilistically favoring certain (“close to optimal”) data transmissions. Our work is inspired and builds upon the directed diffusion paradigm of [7]. This protocol is very simple, uses only local information and operates under total absence of co-ordination between sensors. As shown by extensive experiments we have carried out, the protocol is very energy efficient while achieving high success rates.