Gossiping refers to the following task: In a group of individuals connected by a communication network, every node has a piece of information and needs to transmit it to all the nodes in the network. The networks are modeled by graphs, where the vertices represent the nodes, and the edges, the communication links. In this paper, we concentrate on minimum gossip graphs of even order, that is, gr...

We consider a recent model in which agents hold opinions about each other and influence other’s during random pair interactions. When the are initially close, on short term, all tend to increase over time. On contrary, when very unequal, of high status increase, but low stagnate without gossip decrease with gossip. derive moment approximation average opinion changes that explains these observat...

Many ad hoc routing algorithms rely on broadcast flooding for location discovery or, more generally, for secure routing applications. Flooding is a robust algorithm but because of its extreme redundancy, it is impractical in dense networks. Indeed in large wireless networks, the use of flooding algorithms may lead to broadcast storms where the number of collisions is so large that it causes sys...

We propose a gossip-based distributed algorithm for Gaussian mixture learning, Newscast EM. The algorithm operates on network topologies where each node observes a local quantity and can communicate with other nodes in an arbitrary point-to-point fashion. The main difference between Newscast EM and the standard EM algorithm is that the M-step in our case is implemented in a decentralized manner...

Curiosity and gossip often underline human activities social behavior. Gossip can work as an instrument of power, controlling people's actions but it actively play a role in migration intentions? Migration studies focus on structural economic factors that influence decisions to relocate, socio-cultural such are not included. is considered fixed, given characteristic small close-knit communities...