Selfish Distributed Compression over Networks: Correlation Induces Anarchy

TL;DR

This paper investigates how selfish behavior among terminals in correlated source multicast networks can lead to inefficiencies, quantified by the Price of Anarchy, which can be significantly higher than in independent source scenarios.

Contribution

It characterizes the impact of source correlation on the Price of Anarchy in distributed network compression, providing bounds and explicit examples demonstrating increased inefficiency.

Findings

Source correlation can significantly increase the Price of Anarchy.

Explicit examples show POA > 1 due to correlation.

Derived near-tight bounds on the Price of Anarchy.

Abstract

We consider the min-cost multicast problem (under network coding) with multiple correlated sources where each terminal wants to losslessly reconstruct all the sources. We study the inefficiency brought forth by the selfish behavior of the terminals in this scenario by modeling it as a noncooperative game among the terminals. The degradation in performance due to the lack of regulation is measured by the {\it Price of Anarchy} (POA), which is defined as the ratio between the cost of the worst possible \textit{Wardrop equilibrium} and the socially optimum cost. Our main result is that in contrast with the case of independent sources, the presence of source correlations can significantly increase the price of anarchy. Towards establishing this result, we first characterize the socially optimal flow and rate allocation in terms of four intuitive conditions. Next, we show that the Wardrop equilibrium is a socially optimal solution for a different set of (related) cost functions. Using this, we construct explicit examples that demonstrate that the POA $> 1$ and determine near-tight upper bounds on the POA as well. The main techniques in our analysis are Lagrangian duality theory and the usage of the supermodularity of conditional entropy.