Jingwei: An Efficient and Adaptable Data Migration Strategy for Deduplicated Storage Systems

Cheng, Geyao; Guo, Deke; Luo, Lailong; Xia, Junxu; Sun, Yuchen

doi:10.1109/infocom48880.2022.9796954

Cited by 4 publications

(3 citation statements)

References 19 publications

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“…A preliminary version of this article was accepted in IN-FOCOM 2022 [1]. This version further considered the heat variation, and innovatively proposed adjustment strategies to alleviate performance degradation caused by heat changes.…”

Section: Acknowledgmentsmentioning

confidence: 99%

“…The illustrative examples of the Jingwei strategy and some existing methods [7], [17]. Four files (f 1 ∼ f 4 ), which are attached with heat degrees (1,8,6,7), are partitioned into five blocks (b 1 ∼ b 5 ). The ambition is to migrate a part of the four files from server 1 to server 2. hot files, may impact the service adaptability significantly in practice [2].…”

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confidence: 99%

“…Inspired by these observations, in this paper, we propose Jingwei, 1 an efficient and adaptive data migration strategy for deduplicated storage systems. Jingwei realizes a proper trade-off between the space efficiency (minimizing data replication in the migration process) and the service adaptability (building replicas of hot files to spread the frequent data access requirements).…”

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confidence: 99%

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When Deduplication Meets Migration: An Efficient and Adaptive Strategy in Distributed Storage Systems

Cheng

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Xia

et al. 2023

IEEE Trans. Parallel Distrib. Syst.

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The traditional migration methods are confronted with formidable challenges when data deduplication technologies are incorporated. First, the deduplication creates data-sharing dependencies in the stored files; breaking such dependencies in migration may attach extra space overhead. Second, the redundancy elimination makes the storage system reserves only one copy for each storage file, and heightens the risk of data unavailability. The existing methods fail to tackle them in one shot. To this end, we propose Jingwei, an efficient and adaptive data migration strategy for deduplicated storage systems. To be specific, Jingwei tries to minimize the extra space cost in migration for space efficiency. Meanwhile, Jingwei realizes the service adaptability by encouraging replicas of hot files to spread out their data access requirements. We first model such a problem as an integer linear programming (ILP) and solve it with a commercial solver when only one empty migration target server is allowed. We then extend this problem to a scenario wherein multiple non-empty target servers are available for migration. We solve it by effective heuristic algorithms based on the Bloom Filter-based data sketches. The Jingwei strategy can suffer from performance degradation when the heat degree varies significantly. Therefore, we further present incremental adjustment strategies for the two scenarios, which adjust the number of block replicas and their locations in an incremental manner. The mathematical analyses and trace-driven experiments show the effectiveness of our Jingwei strategy. To be specific, Jingwei fortifies the file replicas by 25% with only 5.7% of the extra storage space, compared with the latest "Goseed" method. With the small extra space cost, the file retrieval throughput of Jingwei can reach up to 333.5 Mbps, which is 12.3% higher than that of the Random method.

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Section: Acknowledgmentsmentioning

confidence: 99%

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confidence: 99%

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confidence: 99%

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When Deduplication Meets Migration: An Efficient and Adaptive Strategy in Distributed Storage Systems

Cheng

Luo

Xia

et al. 2023

IEEE Trans. Parallel Distrib. Syst.

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The Doctrine of MEAN: Realizing Deduplication Storage at Unreliable Edge

Xia

Cheng

Luo

et al. 2023

IEEE Trans. Parallel Distrib. Syst.

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LaDy: Enabling L ocality- a ware D eduplication Technolog y on Shingled Magnetic Recording Drives

Chang,

Shih

et al. 2023

ACM Trans. Embed. Comput. Syst.

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The continuous increase in data volume has led to the adoption of shingled-magnetic recording (SMR) as the primary technology for modern storage drives. This technology offers high storage density and low unit cost but introduces significant performance overheads due to the read-update-write operation and garbage collection (GC) process. To reduce these overheads, data deduplication has been identified as an effective solution as it reduces the amount of written data to an SMR-based storage device. However, deduplication can result in poor data locality, leading to decreased read performance. To tackle this problem, this study proposes a data locality-aware deduplication technology, LaDy, that considers both the overheads of writing duplicate data and the impact on data locality to determine whether the duplicate data should be written. LaDy integrates with DiskSim, an open-source project, and modifies it to simulate an SMR-based drive. The experimental results demonstrate that LaDy can significantly reduce the response time in the best-case scenario by 87.3% compared with CAFTL on the SMR drive. LaDy achieves this by selectively writing duplicate data, which preserves data locality, resulting in improved read performance. The proposed solution provides an effective and efficient method for mitigating the performance overheads associated with data deduplication in SMR-based storage devices.

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Jingwei: An Efficient and Adaptable Data Migration Strategy for Deduplicated Storage Systems

Cited by 4 publications

References 19 publications

When Deduplication Meets Migration: An Efficient and Adaptive Strategy in Distributed Storage Systems

When Deduplication Meets Migration: An Efficient and Adaptive Strategy in Distributed Storage Systems

The Doctrine of MEAN: Realizing Deduplication Storage at Unreliable Edge

LaDy: Enabling L ocality- a ware D eduplication Technolog y on Shingled Magnetic Recording Drives

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