Hybrid Block Storage for Efficient Cloud Volume Service

Author:

Zhang Yiming1ORCID,Li Huiba2ORCID,Liu Shengyun3ORCID,Huang Peng4ORCID

Affiliation:

1. NICEX Lab, Xiamen University, China

2. Alibaba Group, China

3. Shanghai Jiao Tong University, China

4. University of Michigan, USA

Abstract

The migration of traditional desktop and server applications to the cloud brings challenge of high performance, high reliability, and low cost to the underlying cloud storage. To satisfy the requirement, this article proposes a hybrid cloud-scale block storage system called Ursa . Trace analysis shows that the I/O patterns served by block storage have only limited locality to exploit. Therefore, instead of using solid state drives (SSDs) as a cache layer, Ursa proposes hybrid storage structure that directly stores primary replicas on SSDs and replicates backup replicas on hard disk drives (HDDs) . At the core of Ursa ’s hybrid storage design is an adaptive journal that can bridge the performance gap between primary SSDs and backup HDDs for random writes by transforming small backup writes into journal appends, which are then asynchronously replayed and merged to backup HDDs. To efficiently index the journal, we design a novel range-optimized merge-tree structure that combines a continuous range of keys into a single composite key {offset,length} . Ursa integrates the hybrid structure with designs for high reliability, scalability, and availability. Experiments show that Ursa in its hybrid mode achieves almost the same performance as in its SSD-only mode (storing all replicas on SSDs), and outperforms other block stores (Ceph and Sheepdog) even in their SSD-only mode while achieving much higher CPU efficiency (IOPS and throughput per core).

Funder

National Key Research and Development Program of China

OS Innovation Lab Project of Xiamen University and Huawei

Publisher

Association for Computing Machinery (ACM)

Subject

Hardware and Architecture

Reference55 articles.

1. Retrieved from http://ceph.com/.

2. Retrieved from http://iotta.snia.org/traces/388.

3. Retrieved from https://aws.amazon.com/ebs/.

4. Retrieved from https://blocksandfiles.com/2020/05/15/enterprise-ssds-are-ten-x-cost-of-nearline-disk-drives/.

5. Retrieved from https://en.wikipedia.org/wiki/Wear_leveling.

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Token Hashing: A High-speed Data Retrieval Hash Index Structure;Proceedings of the 5th International Conference on Computer Information and Big Data Applications;2024-04-26

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