We introduce a framework that can model different kinds of epistemic gossip problems. We also formalize some parameters that distinguish the different types of gossip problem. Finally, we present a few results that show the effect of the parameters.

Gossip protocols have proved to be a viable solution to setup and manage large-scale P2P services or applications in a fully decentralised scenario. The gossip or epidemic communication scheme is heavily based on stochastic behaviors and it is the fundamental idea behind many large-scale P2P protocols. It provides many remarkable features, such as scalability, robustness to failures, emergent l...

Gr oup-based reliable multicast is an important building block for distributed applications. For large systems, however, traditional appr oaches do not scale well due to centr alize drecovery mechanisms and excessive message overhead. In this paper, we present a reliable probabilistic multicast, rpbcast, that is a hybrid of the centr alize dand gossip-b ased approaches. In p articular,rpbcast e...

In this project we look at the effects of gossip spread on social network structure. We define gossip as information passed between two individuals A and B about an individual C who is not present, which has the potential to affect the strengths of all three relationships A-B, B-C, and A-C. This work is novel in two respects: first, there is no theoretical work on how network structure changes ...

It has been recently demonstrated that the classical EM algorithm for learning Gaussian mixture models can be successfully implemented in a decentralized manner by resorting to gossip-based randomized distributed protocols. In this paper we describe a gossip-based implementation of an alternative algorithm for learning Gaussian mixtures in which components are added to the mixture one after ano...