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Preference-Aware Query and Update Scheduling in Web-databases

DocUID: 2007-005 Full Text: PDF

Author: Huiming Qu, Alexandros Labrinidis

Abstract: Typical web-database systems receive read-only queries, that generate dynamic web pages as a response, and write-only updates, that keep information up-to-date. Users expect short response times and low staleness. However, it may be extremely hard to apply all updates on time, i.e., keep zero staleness, and also get fast response times, especially in periods of bursty traffic. In this paper, we present the concept of Quality Contracts (QCs) which combines the two incomparable performance metrics: response time or Quality of Service (QoS), and staleness or Quality of Data (QoD). QCs allows individual users to express their preferences for the expected QoS and QoD of their queries by assigning ``profit" values. To maximize the total profit from submitted QCs, we propose an adaptive algorithm, called QUTS. QUTS addresses the problem of prioritizing the scheduling of updates over queries using a two-level scheduling scheme that dynamically allocates CPU resources to updates and queries according to user preferences. We present the results of an extensive experimental study using real data (taken from a stock information web site), where we show that QUTS performs better than baseline algorithms under the entire spectrum of QCs; QUTS also adapts fast to changing workloads.

Published In: Proc. of the 23rd IEEE International Conference on Data Engineering

Pages: pp. 1-10

Place Published: Istanbul, Turkey

Year Published: 2007

Project: UserCentric Subject Area: Web Databases

Publication Type: Conference Paper

Sponsor: NSF ITR ANI-0325353

Citation:Text Latex BibTex XML Huiming Qu, and Alexandros Labrinidis. Preference-Aware Query and Update Scheduling in Web-databases, Proc. of the 23rd IEEE International Conference on Data Engineering (ICDE'07), pp. 1-10, Istanbul, Turkey, April 2007.