Abstract
Cloud storage system usually experiences data loss, hindering data durability. Three-way random replication is commonly used to prevent data loss in cloud storage systems. However, it cannot effectively handle correlated machine failures. Although Copyset Replication and Tiered Replication can reduce data loss in correlated and independent failures and enhance data durability, they fail to leverage different data popularities to substantially reduce the storage cost and bandwidth cost caused by replication. To address these issues, we present a popularity-aware multi-failure resilient and cost-effective replication (PM-CR) scheme for high data durability in cloud storage. PMCR splits the cloud storage system into primary tier and backup tier, and classifies data into hot data, warm data and cold data based on data popularities. To handle both correlated and independent failures, PMCR stores the three replicas of the same data into one Copyset formed by two servers in the primary tier and one server in the backup tier. For the third replicas of warm data and cold data in the backup tier, PMCR uses the Similar Compression method for read-intensive data and uses the Delta Compression method for write-intensive data to reduce storage cost and bandwidth cost. As a result, these costs are reduced and data durability and availability are enhanced without compromising data request delay greatly. Extensive experiment results based on trace parameters show that PMCR achieves high data durability, low probability of data loss, and low storage cost and bandwidth cost compared to previous replication schemes.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.