Statistical Characterizers of Transport in a Communication Network

TL;DR

This paper identifies statistical signatures, specifically Gaussian and log-normal distributions, that distinguish congested and decongested phases in various communication network models, aiding phase identification.

Contribution

It demonstrates that travel time distributions serve as reliable indicators of congestion states across diverse network topologies and strategies.

Findings

Gaussian travel time distribution in congestion

Log-normal distribution in decongestion

Distribution patterns correctly identify network phases

Abstract

We identify the statistical characterizers of congestion and decongestion for message transport in model communication lattices. These turn out to be the travel time distributions, which are Gaussian in the congested phase, and log-normal in the decongested phase. Our results are demonstrated for two dimensional lattices, such the Waxman graph, and for lattices with local clustering and geographic separations, gradient connections, as well as for a 1-d ring lattice with random assortative connections. The behavior of the distribution identifies the congested and decongested phase correctly for these distinct network topologies and decongestion strategies. The waiting time distributions of the systems also show identical signatures of the congested and decongested phases.