Online virtual machine migration for renewable energy usage maximization in geographically distributed cloud datacenters

Abstract

Energy consumption and its associated costs represent a huge part of cloud providers' operational costs. In this study, we explore how much energy cost savings can be made knowing the future level of renewable energy (solar/wind) available in data centers. Since renewable energy sources have intermittent nature, we take advantage of migrating virtual machines to the nearby data centers with excess renewable energy. In particular, we first devise an optimal offline algorithm with full future knowledge of renewable level in the system. Since in practice, accessing long-term and exact future knowledge of renewable energy level is not feasible, we propose two online deterministic algorithms, one..