## Abstract

We consider information dissemination over a network of gossiping agents. In this model, a source keeps the most up-to-date information about a time-varying binary state of the world, and n receiver nodes want to follow the information at the source as accurately as possible. When the information at the source changes, the source first sends updates to a subset of (Formula presented.) nodes. Then, the nodes share their local information during the gossiping period, to disseminate the information further. The nodes then estimate the information at the source, using the majority rule at the end of the gossiping period. To analyze the information dissemination, we introduce a new error metric to find the average percentage of nodes that can accurately obtain the most up-to-date information at the source. We characterize the equations necessary to obtain the steady-state distribution for the average error and then analyze the system behavior under both high and low gossip rates. We develop an adaptive policy that the source can use to determine its current transmission capacity m based on its past transmission rates and the accuracy of the information at the nodes. Finally, we implement a clustered gossiping network model, to further improve the information dissemination.

Original language | English (US) |
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Article number | 9 |

Journal | Entropy |

Volume | 26 |

Issue number | 1 |

DOIs | |

State | Published - Jan 2024 |

## Keywords

- information dissemination
- Markov chains
- social networks
- gossiping effect
- gossip networks

## ASJC Scopus subject areas

- Information Systems
- Mathematical Physics
- Physics and Astronomy (miscellaneous)
- General Physics and Astronomy
- Electrical and Electronic Engineering