Fair non-monetary scheduling in federated clouds

TL;DR

This paper introduces CloudShare, a distributed load balancing algorithm for federated clouds that uses game theory to ensure fair resource sharing without monetary transactions, demonstrated through simulation.

Contribution

It presents CloudShare, a novel distributed load balancing approach based on the Shapley value, promoting fairness among cloud service providers in federated clouds.

Findings

CloudShare achieves more fair schedules than FairShare.

Simulation results validate the effectiveness of CloudShare.

Provides an alternative to monetary resource sharing methods.

Abstract

In a hybrid cloud, individual cloud service providers (CSPs) often have incentive to use each other's resources to off-load peak loads or place load closer to the end user. However, CSPs have to keep track of contributions and gains in order to disincentivize long-term free-riding. We show CloudShare, a distributed version of a load balancing algorithm DirectCloud based on the Shapley value---a powerful fairness concept from game theory. CloudShare coordinates CSPs by a ZooKeeper-based coordination layer; each CSP runs a broker that interacts with local resources (such as Kubernetes-managed clusters). We quantitatively evaluate our implementation by simulation. The results confirm that CloudShare generates on the average more fair schedules than the popular FairShare algorithm. We believe our results show an viable alternative to monetary methods based on, e.g., spot markets.