We present a game theoretic approach for power reduction in large-scale distributed storage systems. The key idea is to use a distributed hash table and migrate its virtual nodes dynamically so as to skew the workload towards a subset of physical disks while not overloading them. To realize this idea in an autonomous way, virtual nodes are regarded as selfish agents playing a game in which each node receives a payoff according to the workload of the disk on which it currently resides. We model this setting as a potential game, a kind of strategic game in which the incentive of all players to change their strategy can be represented by a single global function. Thus, any increase in the payoff of a virtual node yields a better state in terms of energy conservation. This game model consists of a pair of global and private payoff functions, derived by the Wonderful Life Utility scheme. The former function evaluates how good the current state of the system is, while the latter determines the current payoff of each node. The performance of our method is measured both by simulations and a prototype implementation. From the experiments, we observed that our method consumed 11.1%-16.4% less energy than the static configuration. In addition, although a small number of responses were heavily delayed because of overloading of some disks at peak time, our method maintained preferred overall average response time in the range 50-190ms.
2016 by the Information Processing Society of Japan