eWave:利用在线重复数据删除集群的能量感知

Raúl Gracia-Tinedo, M. Sánchez-Artigas, P. García-López
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引用次数: 2

摘要

内嵌式重复数据删除集群为企业和组织提供高吞吐量和可扩展的存储/归档服务。不幸的是,由于超级块路由的并行特性,高吞吐量的代价是在每个请求上激活几个存储节点。这可能会阻止存储节点利用磁盘待机时间来保存能量,即使在低负载期间也是如此。我们的目标是使重复数据删除集群能够利用负载谷来节省磁盘能量。为此,我们将探讨在这种情况下延迟写、分流访问和工作负载整合的可行性。我们在eWave中实现了我们的见解:一种用于重复数据删除集群的新型节能存储中间件。eWave的主要目标是在不修改重复数据删除层的情况下实现重复数据删除集群的能量感知操作。通过在8台机器集群中的广泛模拟和实验,我们表明eWave在低负载期间对性能有中等影响的普通场景下将磁盘能量从16%减少到60%。
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eWave: Leveraging Energy-Awareness for In-line Deduplication Clusters
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.
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