On the TradeOff Between Performance and Storage Efficiency of ReplicationBased Object Storage The object storage systems are used to store and manage unstructured data. Most object storage systems provide the replication policy (REP) or erasure code policy (EC) to ensure the reliability and availability of data. In this paper, we study the tradeoff between performance and storage efficiency of these policies with respect to different data sizes of user requests. To this end, we present a hybrid policy management system that takes advantage of both policies by automatically changing policy based on data size. We have implemented the hybrid system in OpenStack Swift. Our evaluation results show the throughput of GET request increases up to 36% while improving storage efficiency by up to 53% compared to that using the REP policy.

StorageReliabilityRepair TradeOffs in Distributed Storage System For reliability purpose, data redundancy is anessential in distributed storage system. In the evolving of data redundancy schemes, storagereliabilityrepair tradeoffs always exist. From replication to erasure codes, higher reliability achieves with lower storage cost, but the higher repair penalty can not be ignored. Optimized data redundancy schemes like regenerating codes or basic pyramid codes are proposed to relieve the high repair penalty. In order to study the storagereliabilityrepair tradeoffs, we propose a new model based on the standard Markov Chain, it takes the irregular fault tolerance, latent sector error and correlated failures into account, and measures the storage and repair cost from system perspective. Through interscheme and intrascheme discussions, we find some principles about choosing data redundancy schemes and corresponding parameters to achieve better storagereliabilityrepair tradeoffs. Our goal is to provide system designers and administrators with concrete information to help them achieve proper storagereliabilityrepair tradeoffs.