QUERY PLANNING FOR CONTINUOUS AGGREGATION QUERIES USING DATA AGGREGATORS
Journal Title: International Journal of Advanced Research in Computer Engineering & Technology(IJARCET) - Year 2013, Vol 2, Issue 8
Abstract
Continuous aggregation queries are used to monitor the changes in data with time varying for online decision making. For contin uous queries low cost and scalable technique s used a network of aggregators. Individual node cannot by itself determine its inclusion in the query result for this a different algorithmic challenges from aggregate and selection queries are presented. At spe cific coherencies each data item can serve for a set of data aggregators. Technique involves disseminating query into sub query and sub queries are executed on the chosen data aggregators. We build a query cost model which can be used to estimate the numbe r of refresh messages which is required to satisfy the client specified incoherency bound. Performance results shows that by our method the query can be executed using less than one third the messages required for existing schemes. Our adaptive strategy em ploys distributed decisions made by the distributed servers independently based on localized statistics collect ed by each server at runtime. When comparatively static environment, pro pose two motionless tree construction algorithms relying on apriori syst em statistics. These static trees can also be used as early tr ees in a dynamic environment and apply our schemes to both single - and multi object distribution . Our extensive performance study illustrate that the adaptive mechanisms
Authors and Affiliations
A . S ATEESH , D. ANIL , M. KIRAN KUMAR
Keywords
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