Broadcasting and gossiping are fundamental communication tasks in networks. In broadcasting, one node of a network has a message that must be learned by all other nodes. In gossiping, every node has a (possibly different) message, and all messages must be learned by all nodes. We study these well-researched tasks in a very weak communication model, called the beeping model. Communication procee...

Radio networks model wireless synchronous communication with only one wave frequency used for transmissions. In the problem of many-to-all (M2A) communication, some nodes hold input rumors, and the goal is to have all nodes learn all the rumors. We study the average time complexity of distributed many-to-all communication by deterministic protocols in directed networks under two scenarios: of c...

We introduce a technique for accelerating the gossip algorithm of Boyd et. al. (INFOCOM 2005) for distributed averaging in a network. By employing memory in the form of a small shift-register in the computation at each node, we can speed up the algorithm’s convergence by a factor of 10. Our accelerated algorithm is inspired by the observation that the original gossip algorithm is analogous to t...

Cím: A comparative study of spanning tree and gossip protocols for aggregation

This paper focuses on monitoring the state of the nodes in a wireless sensor network where the nodes are unaware of the location of the monitoring node. We introduce an epidemic protocol designed to propagate the state of the nodes in a simple, yet effective manner. The nodes in the network communicate their state through local interaction with their neighbors. The monitoring of the network is ...