A Packet Dropping Mechanism for Efficient Operation of M/M/1 Queues with Selfish Users

TL;DR

This paper introduces a packet dropping mechanism in M/M/1 queue games with selfish users, improving efficiency by aligning individual incentives with social welfare, and demonstrates convergence to optimal equilibria.

Contribution

It proposes a simple packet dropping scheme that transforms the game into an ordinal potential game with near-optimal social welfare at equilibrium.

Findings

The mechanism results in a unique Nash Equilibrium.

The best response dynamics converge to this equilibrium.

Social welfare at equilibrium can be arbitrarily close to the optimal.

Abstract

We consider a fundamental game theoretic problem concerning selfish users contributing packets to an M/M/1 queue. In this game, each user controls its own input rate so as to optimize a desired tradeoff between throughput and delay. We first show that the original game has an inefficient Nash Equilibrium (NE), with a Price of Anarchy (PoA) that scales linearly or worse in the number of users. In order to improve the outcome efficiency, we propose an easily implementable mechanism design whereby the server randomly drops packets with a probability that is a function of the total arrival rate. We show that this results in a modified M/M/1 queueing game that is an ordinal potential game with at least one NE. In particular, for a linear packet dropping function, which is similar to the Random Early Detection (RED) algorithm used in Internet Congestion Control, we prove that there is a unique NE. We also show that the simple best response dynamic converges to this unique equilibrium. Finally, for this scheme, we prove that the social welfare (expressed either as the summation of utilities of all players, or as the summation of the logarithm of utilities of all players) at the equilibrium point can be arbitrarily close to the social welfare at the global optimal point, i.e. the PoA can be made arbitrarily close to 1. We also study the impact of arrival rate estimation error on the PoA through simulations.