An Online Algorithm for Power-proportional Data Centers with Switching Cost

TL;DR

This paper presents an online algorithm for dynamically managing heterogeneous data centers to optimize energy costs, incorporating switching costs and outperforming existing greedy algorithms based on real workload simulations.

Contribution

Introduces a novel online algorithm with regularization for power-proportional data centers, extending to include switching costs and demonstrating improved performance.

Findings

Outperforms greedy algorithms in simulations

Achieves better competitive ratio

Effectively manages heterogeneous data center costs

Abstract

Recent studies have shown that power-proportional data centers can save energy cost by dynamically "right-sizing" the data centers based on real-time workload. More servers are activated when the workload increases while some servers can be put into the sleep mode during periods of low load. In this paper, we revisit the dynamic right-sizing problem for heterogeneous data centers with various operational cost and switching cost. We propose a new online algorithm based on a regularization technique, which achieves a better competitive ratio compared to the state-of-the-art greedy algorithm. We further introduce a switching cost offset into the model and extend our algorithm to this new setting. Simulations based on real workload and renewable energy traces show that our algorithms outperform the greedy algorithm in both settings.