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ABSTRACT
Accessing and processing distributed data sources have become important factors for businesses today. This is especially true for the emerging virtual enterprises with their data and processing capabilities spread across the Internet. Unfortunately, however, query processing on the Internet is not predictable and robust enough to meet the requirements of many business applications. For instance, the response time of a query can be unexpectedly high; or the monetary cost might be too high if the partners charge for the usage of their data or processing capabilities; or the result of the query might be useless because it is based on outdated data or only on parts (rather than all) of the available data. In this work, we show how a distributed query processor can be extended in order to support quality of service (QoS) guarantees. We propose ways to integrate QoS management into the various phases of query processing: (1) Query optimization uses a multi-dimensional assessment (cost, time and result quality) of query plans, (2) query plan instantiation comprises an admission control for sub-plans, and (3) during query plan execution the QoS of the query is monitored and a fuzzy controller initiates repairing actions if needed. The goal of our work is to provide an initial step towards QoS management in distributed query processing systems and do significantly better than current distributed database systems, which are based on a best-effort policy.
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CITED BY 7
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Tobias Scholl , Bernhard Bauer , Benjamin Gufler , Richard Kuntschke , Daniel Weber , Angelika Reiser , Alfons Kemper, HiSbase: histogram-based P2P main memory data management, Proceedings of the 33rd international conference on Very large data bases, September 23-27, 2007, Vienna, Austria
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Tobias Scholl , Bernhard Bauer , Benjamin Gufler , Richard Kuntschke , Angelika Reiser , Alfons Kemper, Scalable community-driven data sharing in e-science grids, Future Generation Computer Systems, v.25 n.3, p.290-300, March, 2009
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