Abstract
The increasing and widespread use of web services, usually represented by database queries, is putting a strain on web database systems behind them. In such systems web services are associated with soft-deadlines, and the success of these systems (i.e., the user satisfaction) is better measured in terms of minimizing the deviation from the deadline, that is, tardiness. Previous work on query scheduling focused on ordering the execution of independent queries while ignoring the commonality among queries, such that a same work will be computed multiple times which can impact user satisfaction negatively. This paper proposes a new query scheduling framework which incorporates semantic caching techniques into the query scheduling procedure. We develop a query splitting-based strategy to discover common sub-expressions among queries and design a sharing-aware query scheduling algorithm GASA which minimizes average tardiness while reducing redundant work at the same time. We experimentally compare our approach with state-of-the-art methods on TPC-H workloads. Our experimental results show that our method can efficiently and effectively minimize average tardiness of a large number of data service requests.
This work is supported by National Natural Science Foundation of China under Grant No.61202035 and No. 61232002.
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Jiang, J., Peng, Z., Wu, X., Liang, N. (2014). Sharing-Aware Scheduling of Web Services. In: Chen, L., Jia, Y., Sellis, T., Liu, G. (eds) Web Technologies and Applications. APWeb 2014. Lecture Notes in Computer Science, vol 8709. Springer, Cham. https://doi.org/10.1007/978-3-319-11116-2_14
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DOI: https://doi.org/10.1007/978-3-319-11116-2_14
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