Exploring A Forecasting Structure for the Capacity Usage in Backup Storage Systems Protecting data from loss is important in many domains, particularly business. Businesses generally employ thirdparty protection services to routinely back up data to storage. As the scale of the backup system and the volume of backup data continue to grow significantly, backup jobs fail increasingly frequently. In this study, we present an analysis of data protection system reports written over two years and collected from 3,500 backup systems. We found that inadequate capacity is among the two most frequent causes of the failure of backups. Little research has targeted the development of a forecasting tool to predict the backup storage capacity to mitigate this failure, and accurate prediction becomes more challenging as the number of clients served by the storage increases. Our research highlights the characteristics of enterprise backup storage data and uses the information examined here to develop a forecasting structure. We tested our forecasting structure on empirically obtained data. In comparison with a prevalent backup system forecasting tool, our structure provides better and more robust predictions of the capacity of backup storage systems as well as the size of data generated by a given number of clients and the associated deduplication ratios.

RepECDuet: Ensure High Reliability and Performance for Deduplicated and DeltaCompressed Storage Systems Data deduplication is a widely deployed technique to remove duplicate content to save storage space, which is however incapable of eliminating the redundancy between nonidentical but similar data blocks. To achieve further space savings in deduplicated storage systems, delta compression is employed to compress postdeduplication data. Both deduplication and delta compression introduce content references among blocks, which inevitably undermines the reliability of deduplicated and delta compressed storage systems. To ensure better reliability, existing approaches utilize either replication or erasure codes to redundantly distribute data across multiple nodes. In deduplicated and delta compressed storage systems, we observe that delta compressed chunks (DCCs) are far smaller than regular chunks called nonDCCs. Motivated by this observation, we suggest a straightforward approach in which replication is used to protect DCCs and erasure code is deployed to protect nonDCCs. However, we need to address two critical challenges to ensure this solution effective. First, the random placement of DCCs replicas destroys cache locality. Second, the separate and individual recovery and restore cache could cause storage containers to be accessed repeatedly. To address these two challenges, in this paper, we propose RepECDuet which employs both replication and erasure codes to ensure high reliability and performance for deduplicated and deltacompressed storage systems. RepECDuet introduces a deltautilizationaware filter to select and replicate containers based on the percentage of DCCs in the containers to maintain cache locality. Moreover, to avoid unnecessary container reads, we design a cooperative cache scheme that is aware of both failure recovery and regular restore cache. Our experimental results based on three realworld datasets demonstrate that RepECDuet significantly improves the restore performance by 26%59%, and reduces the storage overhead by 54%98% than the existing approaches.