Pareto-optimal Nash equilibrium in capacity allocation game for self-managed networks

TL;DR

This paper introduces a capacity allocation game modeling self-managed networks, providing a decentralized algorithm to compute Pareto-optimal Nash equilibria and analyzing their efficiency.

Contribution

It presents a novel game-theoretic framework for capacity allocation in self-managed networks with an efficient decentralized solution method.

Findings

The algorithm computes strongly Pareto-optimal strategies.

Analysis of Price of Anarchy and Price of Stability.

Experimental validation of the proposed approach.

Abstract

In this paper we introduce a capacity allocation game which models the problem of maximizing network utility from the perspective of distributed noncooperative agents. Motivated by the idea of self-managed networks, in the developed framework decision-making entities are associated with individual transmission links, deciding on the way they split capacity among concurrent flows. An efficient decentralized algorithm is given for computing strongly Pareto-optimal strategies, constituting a pure Nash equilibrium. Subsequently, we discuss the properties of the introduced game related to the Price of Anarchy and Price of Stability. The paper is concluded with an experimental study.