A Hypergraph Approach to Distributed Broadcast

TL;DR

This paper introduces a hypergraph-based method for distributed broadcast, establishing theoretical bounds and proposing an optimal algorithm for quasi-trees, improving data dissemination efficiency in decentralized networks.

Contribution

It presents a new hypergraph approach to the distributed broadcast problem, including a lower bound and an optimal algorithm for quasi-trees.

Findings

Established a lower bound using hypergraph min-cut capacity.

Developed the DBQT algorithm for quasi-trees, proven to be optimal.

Applicable to various real-world network systems.

Abstract

This paper explores the distributed broadcast problem within the context of network communications, a critical challenge in decentralized information dissemination. We put forth a novel hypergraph-based approach to address this issue, focusing on minimizing the number of broadcasts to ensure comprehensive data sharing among all network users. The key contributions of this work include the establishment of a general lower bound for the problem using the min-cut capacity of hypergraphs, and a distributed broadcast for quasi-trees (DBQT) algorithm tailored for the unique structure of quasi-trees, which is proven to be optimal. This paper advances both network communication strategies and hypergraph theory, with implications for a wide range of real-world applications, from vehicular and sensor networks to distributed storage systems.