This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
27th International Conference on Distributed Computing Systems (ICDCS '07)
Efficient Execution of Continuous Incoherency Bounded Queries over Multi-Source Streaming Data
Toronto, Canada
June 25-June 27
ISBN: 0-7695-2837-3
Manish Bhide, IBM Research, India
Krithi Ramamritham, IIT Bombay, India
Mukund Agrawal, Symantec Corporation, India
On-line decision making often involves query processing over time-varying data which arrives in the form of data streams from distributed locations. In such environments typically, a user application is interested in the value of some function defined over the data items. For example, the traffic management system can make control decisions based on the observed traffic at major intersections; stock investors can manage their investments based on the value of their portfolios. In this paper we present a system that supports pull based data refresh and query processing techniques where such queries access data from multiple distributed sources. Key challenges in supporting such Continuous Multi-Data Incoherency BoundedQueries lie in minimizing network and source overheads, without loss of fidelity in the query responses provided to users. We address these challenges by using mathematically sound approaches based on Gradient Descent and Constraint Optimization which allow us to adapt the refresh frequencies of the dynamically changing data and adjust the quality of service provided to different users.
Index Terms:
orig-research
Citation:
Manish Bhide, Krithi Ramamritham, Mukund Agrawal, "Efficient Execution of Continuous Incoherency Bounded Queries over Multi-Source Streaming Data," icdcs, pp.11, 27th International Conference on Distributed Computing Systems (ICDCS '07), 2007
Usage of this product signifies your acceptance of the Terms of Use.