# Timely Opportunistic Gossiping in Dense Networks

arXiv: https://arxiv.org/abs/2301.00798 · HTML: https://mlsanity.com/paper/2301.00798/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Jan 2023.

## Built on by (most cited first, 2 of 2)

- [Scale-Robust Timely Asynchronous Decentralized Learning](https://mlsanity.com/paper/2404.19749/) (2024)
- [A Learning Based Scheme for Fair Timeliness in Sparse Gossip Networks](https://mlsanity.com/paper/2310.01396/) (2023)

## Abstract (arXiv)

We consider gossiping in a fully-connected wireless network consisting of n nodes. The network receives Poisson updates from a source, which generates new information. The nodes gossip their available information with the neighboring nodes to maintain network timeliness. In this work, we propose two gossiping schemes, one semi-distributed and the other one fully-distributed. In the semi-distributed scheme, the freshest nodes use pilot signals to interact with the network and gossip with the full available update rate B. In the fully-distributed scheme, each node gossips for a fixed amount of time duration with the full update rate B. Both schemes achieve O(1) age scaling, and the semi-distributed scheme has the best age performance for any symmetric randomized gossiping policy. We compare the results with the recently proposed ASUMAN scheme, which also gives O(1) age performance, but the nodes need to be age-aware.