A Price-Anticipating Resource Allocation Mechanism for Distributed Shared Clusters

TL;DR

This paper analyzes a decentralized market-based resource allocation system for shared clusters, demonstrating that it quickly reaches a fair and efficient equilibrium balancing individual utility and overall system performance.

Contribution

It introduces a fixed budget resource allocation game model and shows that the proposed mechanism balances efficiency and fairness at equilibrium.

Findings

System converges rapidly to equilibrium

Achieves a good balance of efficiency and fairness

Outperforms social optimum in fairness measures

Abstract

In this paper we formulate the fixed budget resource allocation game to understand the performance of a distributed market-based resource allocation system. Multiple users decide how to distribute their budget (bids) among multiple machines according to their individual preferences to maximize their individual utility. We look at both the efficiency and the fairness of the allocation at the equilibrium, where fairness is evaluated through the measures of utility uniformity and envy-freeness. We show analytically and through simulations that despite being highly decentralized, such a system converges quickly to an equilibrium and unlike the social optimum that achieves high efficiency but poor fairness, the proposed allocation scheme achieves a nice balance of high degrees of efficiency and fairness at the equilibrium.