eWave: Leveraging Energy-Awareness for In-line Deduplication Clusters

Abstract

In-line deduplication clusters provide high throughput and scalable storage/archival services to enterprises and organizations. Unfortunately, high throughput comes at the cost of activating several storage nodes on each request, due to the parallel nature of superchunk routing. This may prevent storage nodes from exploiting disk standby times to preserve energy, even for low load periods. We aim to enable deduplication clusters to exploit load valleys to save up disk energy. To this end, we explore the feasibility of deferred writes, diverted access and workload consolidation in this setting. We materialize our insights in eWave: a novel energy-efficient storage middleware for deduplication clusters. The main goal of eWave is to enable the energy-aware operation of deduplication clusters without modifying the deduplication layer. Via extensive simulations and experiments in an 8--machine cluster, we show that eWave reduces disk energy from 16% to 60% in common scenarios with moderate impact on performance during low load periods.