Currently, Storage-as-a-Service (StaaS) clouds offer multiple data storage and access pricing options which usually consist of hot and cold tiers. The cold tier storage option offers a lower storage price while the hot tier storage option offers a lower access price. Cloud users need to choose an optimal tier to store their data objects economically based on the frequency of accesses to their data objects. Besides,StaaS cloud users can transfer data objects between these two tiers to save cost according to the varying frequency of accesses to their data objects. Therefore, in order to make optimal transferring decisions,future access curves are needed to be predicted. However, for cloud users, it is difficult to precisely predict future access frequencies for their data objects. In this paper, we propose an online algorithm to guide StaaS cloud users in making decisions on whether and when to transfer their data objects between cold and hot tiers for achieving cost optimizations, while users do not need to have any prior knowledge of future access frequencies. We prove theoretically that the proposed online algorithm can achieve guaranteed competitive ratios for data objects stored in a two-tier StaaS cloud. Finally, through extensive experiments, we validate the effectiveness of our proposed online algorithm and show that it can save costs significantly compared with always keeping data objects in one tier or always transferring data objects from one tier to the other when their access frequencies begin to vary.
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