Abstract
With the emergence of cloud computing and big data, many companies are increasingly relying on the cloud to store and retrieve tremendous amounts of data to leverage the scalability and performance offered by cloud storage services. As a result, data retrieval time has become of a paramount importance for cloud users especially. However, current data management systems are still not optimized to reduce such time. In this paper, we present a deadline-aware data request scheduling scheme, called DAReSch, that aims at scheduling data requests in order to minimize data transfer times and to meet the deadlines specified by the users. We show through real experiments using OpenStack storage system (i.e., Swift) that, compared with the traditional Swift Client system, DAReSch significantly increases the percentage of requests meeting their deadlines, reduces data transfer time, and maximizes bandwidth usage. Furthermore, we also study the impact of the request deadlines on the studied performance metrics. Our extensive experiments show that, when deadlines are stringent, DAReSh allows 60% of the requests to meet their deadline requirements compared with only 10% for the existing solution. When the deadline is less stringent, 90% of the requests can meet their deadline requirements with DAReSh compared with 40% for the existing solution.
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Tlili, G., Yahyaoui, H., Zhani, M.F. et al. DAReSch: deadline-aware request scheduling for cloud storage services. Ann. Telecommun. 74, 545–557 (2019). https://doi.org/10.1007/s12243-019-00728-4
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DOI: https://doi.org/10.1007/s12243-019-00728-4