Technical Report: On the Convergence of Gossip Learning in the Presence of Node Inaccessibility

arXiv:2401.09498v2 Announce Type: replace
Abstract: Gossip learning (GL), as a decentralized alternative to federated learning (FL), is more suitable for resource-constrained wireless networks, such as Flying Ad-Hoc Networks (FANETs) that are formed by unmanned aerial vehicles (UAVs). GL can significantly enhance the efficiency and extend the battery life of UAV networks. Despite the advantages, the performance of GL is strongly affected by data distribution, communication speed, and network connectivity. However, how these factors influence the GL convergence is still unclear. …

abstract aerial arxiv convergence cs.ai cs.lg decentralized efficiency federated learning flying networks node report technical type unmanned aerial vehicles vehicles wireless