Performance Analysis of Probabilistic Flooding Using Random Graphs

Abstract

Probabilistic flooding (parameterized by a forwarding probability) has frequently been considered in the past, as a means of limiting the large message overhead associated with traditional (full) flooding approaches that are used to disseminate globally information in unstructured peer-to-peer and other networks. A key challenge in using probabilistic flooding is the determination of the forwarding probability so that global network outreach is achieved while keeping the message overhead as low as possible. By showing that a probabilistic flooding network generated by applying probabilistic flooding to a connected random graph network can be bounded by properly parameterized random graph networks and invoking random graph theory results, bounds on the value of the forwarding probability are derived guaranteeing global network outreach with high probability, while significantly reducing the message overhead. Bounds on the average number of messages ? as well as asymptotic expressions - and on the average time required to complete network outreach are also derived, illustrating the benefits of the properly parameterized probabilistic flooding scheme.