Energy Cost Minimization in Cloud Datacenter

Abstract

Nowadays, more and more companies migrate business from their own servers to the cloud. With the in ux of computational requests, datacenters consume tremen- dous energy every day, attracting great attention in the energy e ciency dilemma. In this paper, we investigate the energy-aware resource management problem in cloud datacenters, where green energy with unpredictable capacity is considered. Via proposing a robust reinforcement learning-based decentralized resource man- agement framework. Because the reinforcement learning method is informed from the historical knowledge, it relies on no request arrival and energy supply. Ex- perimental results show that our approach is able to reduce the datacenters' cost signi cantly compared with other benchmark algorithms.