Advanced Adaptive Gossiping Using 2-Hop Neighborhood Information

Efficient information dissemination is one of the challenging tasks in most ad-hoc network application domains, be it in wireless sensor networks, mobile ad-hoc networks, or vehicular ad-hoc networks. It is obvious, that flooding has a high communication overhead, leading to channel congestion and packet collisions. Therefore, more efficient dissemination mechanisms were investigated and proposed by the research community. One class of such algorithms is gossiping, where each node forwards a message with a certain probability. The main challenge in gossiping is the proper determination of the forwarding probability, i.e., on the one hand this value has to be chosen high enough to assure a high delivery ratio, on the other hand it has to be as low as possible to reduce communication overhead. At the same time this probability has to be adapted to dynamic network conditions, like changing node density. In this work an advanced scheme for adaptive gossiping is proposed, capable to adjust the dissemination probability dynamically and in a distributed manner. The gossiping probability is determined at a node for every message that has to be forwarded based on two hop neighborhood information. That way, the proposed protocol is capable of working in arbitrary network topologies and densities, enabling more efficient data dissemination compared to existing approaches.