Controlling Gossip Protocol Infection Pattern Using Adaptive Fanout

We propose and evaluate a model for controlling infection patterns defined over rounds or real time in a gossip-based protocol using adaptive fanout. We model three versions of gossip-based protocols: the synchronous protocol, the pseudosynchronous protocol and the asynchronous protocol. Our objective is to ensure that the members of a group receive a desired message within a bounded latency with very high probability. We argue that the most important parameter that controls the latency of message delivery is the fanout used during gossiping, i.e., the number of gossip targets chosen in a particular instance of gossip. We formally analyze the three protocols and provide expressions for fanout. We introduce the idea of using variable fanouts in different rounds in the synchronous protocol. We define fanout as a function of time for the asynchronous protocol such that an expected infection pattern is observed with high probability. For a better understanding of the theoretical model, we develop a pseudosynchronous protocol to highlight the modelling done in order to derive time dependent fanout. We show that our protocols generate Theta(n log n) messages, which is optimal for gossip protocols. We aim to use the gossiping mechanism for large-scale group communication with soft real time constraints. This would alleviate the dependence on tree-based deterministic protocols which usually lack scalability