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Availability Is Not Enough: Minimizing Joint Response Time in Peer-Assisted Cloud Storage Systems

Cloud storage systems have been rapidly emerging recently since they bring fast and convenient storage services to users. We note that providing those service in a private-cloud way is costly, i.e., energy, bandwidth, and storage hardware are expensive for maintaining a cloud storage platform. To cope with the aforementioned issues, our idea is to exploit unused space and bandwidth at user-site machines to build a peer-assisted cloud storage platform. That is, in a peer-assisted cloud storage system, each peer helps back up data of other peers, and all peers form a virtual storage system. However, due to the uneven data popularity and the heterogeneous user upload capacity in peer-to-peer networks, bandwidth-oblivious replica placement might cause extremely long response time for certain data objects. Thus, this paper proposes a new metric called joint response time, which not only considers the waiting time when the requested data are unavailable but also the queuing delay and service time when data become available. We then design a 2-D Markov model to estimate this metric and propose a bandwidth-aware ( BA) replica placement algorithm to reduce the joint response time. Our trace-driven evaluation results validate that the proposed BA algorithm can efficiently utilize the upload capacity of each peer to provide peers a shorter joint response time.