GreenMatch: Renewable-Aware Workload Scheduling for Massive Storage Systems

Abstract

As datacenters grow in scale, increasing energy costs and carbon emissions have led data centers to seek renewable energy, such as wind and solar energy. However, tackling the challenges associated with the intermittent nature and variability of renewable energy is substantial. This paper proposes a scheme called GreenMatch, which deploys an SSD-cache to match green energy supplies with a time-shifting workload schedule while maintaining low latency for online data-intensive services. With the SSD-cache, the process for a latency-sensitive request to access a disk is divided into two stages: a low-energy low-latency online stage and a high-energy high-latency off-line stage. As the process in the latter stage is off-line, it offers opportunities for time-shifting workload scheduling in response to variations of green energy supplies. We also allocate an HDD-cache to guarantee data availability when renewable energy is non-adequate. Furthermore, we design a novel replacement policy called Inactive Disk First for the HDD-cache to avoid inactive disk accesses. The experimental results show that GreenMatch can make full use of renewable energy while minimizing the negative impact of intermittency and variability on performance and availability.