For cloud storage service vendors, balancing the client-perceived IO performance and the self-perceived space cost is always one of the standing challenges. When applying deduplication techniques for the cloud storage systems, the demand for optimizing such tradeoff becomes more pressing. Enabling deduplication decreases the storage space cost, whereas the IO performance will be somewhat affected due to extra processing overhead and data fragmentation. In this article, we address this challenge by proposing MUSE , a MU ti-tiered and S LA-driv E n deduplication framework for cloud storage systems. First, we propose a novel notation of Dedup-SLA (deduplication-oriented service level agreement). With different levels of quantified performance/space-cost combinations, the Dedup-SLA serves as a refined service quality protocol between service vendor and customer. Second, MUSE adopts multi-tiered deduplication that orchestrates several combinational forms of deduplication into multiple tiers with varied “deduplication strength”. Third, we implement a mechanism called dynamic deduplication regulation (DDR) to adjust the deduplication behavior during runtime. MUSE’s deduplication behavior is periodically switched between tiers according to the predefined Dedup-SLA and instant system status. We conduct comprehensive experiments to compare MUSE with several other types of deduplication schemes. The results demonstrate that MUSE significantly optimizes the IO-performance/space-cost balance compared to other schemes, hence delivering higher deduplication service quality for deduplication-enabled cloud storage systems.

中文翻译：

---

MUSE：适用于云存储系统的多层和SLA驱动的重复数据删除框架

对于云存储服务供应商而言，平衡客户端感知的IO性能和自我感知的空间成本始终是长期存在的挑战之一。当将重复数据删除技术应用于云存储系统时，优化这种折衷的需求变得更加紧迫。启用重复数据删除可降低存储空间成本，而IO性能将因额外的处理开销和数据碎片而受到一定影响。在本文中，我们通过提出以下建议来应对这一挑战沉思 ， 一种 亩 分层和 小号 洛杉矶 E n用于云存储系统的重复数据删除框架。首先，我们提出一种新颖的Dedup-SLA表示法（面向重复数据删除的服务水平协议）。通过不同级别的量化性能/空间成本组合，Dedup-SLA可充当服务供应商和客户之间的完善服务质量协议。其次，MUSE采用多层重复数据删除技术，将几种重复数据删除组合形式编排为多层，具有不同的“重复数据删除强度”。第三，我们实现了一种称为动态重复数据删除规则（DDR）的机制，可在运行时调整重复数据删除行为。MUSE的重复数据删除行为会根据预定义的Dedup-SLA和即时系统状态在各层之间定期切换。我们进行了全面的实验，以将MUSE与其他几种重复数据删除方案进行比较。