Euclidean Information Theory of Networks

TL;DR

This paper develops a deterministic information-theoretic model for multi-hop networks to optimize message transmission strategies, analyze feedback benefits, and guide user cooperation for improved network throughput.

Contribution

It introduces a novel deterministic model for multi-hop networks and formulates an optimization framework to maximize throughput and analyze feedback effects.

Findings

Optimal strategies for common message generation

Feedback can enhance transmission efficiency in certain scenarios

Guidelines for user cooperation in multi-layer networks

Abstract

In this paper, we extend the information theoretic framework that was developed in earlier work to multi-hop network settings. For a given network, we construct a novel deterministic model that quantifies the ability of the network in transmitting private and common messages across users. Based on this model, we formulate a linear optimization problem that explores the throughput of a multi-layer network, thereby offering the optimal strategy as to what kind of common messages should be generated in the network to maximize the throughput. With this deterministic model, we also investigate the role of feedback for multi-layer networks, from which we identify a variety of scenarios in which feedback can improve transmission efficiency. Our results provide fundamental guidelines as to how to coordinate cooperation between users to enable efficient information exchanges across them.