In this work we present a new framework for the analysis and design of randomized gossip
algorithms for solving the average consensus problem. We show how classical randomized …

Motivated by applications to sensor, peer-to-peer and ad hoc networks, we study distributed
asynchronous algorithms, also known as gossip algorithms, for computation and information …

In this paper we propose a novel probabilistic broadcast protocol that reduces the average
end-to-end latency by dynamically adapting to network topology and traffic conditions. It …

Gossip protocols have been successfully applied in the last few years to address a wide
range of functionalities. So far, however, very few software frameworks have been proposed …

We develop an analytical model of information dissemination for a gossiping protocol that
combines both pull and push approaches. With this model we analyse how fast an item is …

This paper abstracts the problem of network nodes discovering one another in a network of
unknown size using all-to-all gossip. The problem is studied in terms of evolving directed …

Gossip-based protocols have received considerable attention for broadcast applications due
to their attractive scalability and reliability properties. The reliability of probabilistic gossip …

Gossiping is a distributed process whose purpose is to enable the members of a group of n>
1 autonomous agents to asymptotically determine in a decentralized manner, the average of …

Machine learning over fully distributed data poses an important problem in peer‐to‐peer
applications. In this model, we have one data record at each network node but without the …

Motivated by applications to wireless sensor, peer-to-peer, and ad hoc networks, we study
distributed broadcasting algorithms for exchanging information and for computing in an …