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Typically a user desires to obtain the value of some aggregation function over distributed data items. We present a low-cost, scalable technique to answer continuous aggregation queries using a network of aggregators of dynamic data items. In such a network of data aggregators, each data aggregator serves a set of data items at specific coherencies. Our technique involves decomposing a client query into sub-queries and executing sub-queries on judiciously chosen data aggregators with their individual sub-query incoherency bounds. We provide a technique for getting the optimal set of sub-queries with their incoherency bounds, which satisfies client query’s coherency requirement with least number of refresh messages sent from aggregators to the client. For estimating the number of refresh messages, we build a query cost model which can be used to estimate the number of messages required to satisfy the client specified incoherency bound. Performance results using real-world traces show that our cost based query planning leads to queries being executed using less than one third the number of messages required by existing schemes.
Dr. P. Prabhakar. 2012. \u201cAnalyzing the Query Performance over a Distributed Network of Data Aggregators\u201d. Global Journal of Computer Science and Technology - E: Network, Web & Security GJCST-E Volume 12 (GJCST Volume 12 Issue E14): .
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
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Total Score: 107
Country: India
Subject: Global Journal of Computer Science and Technology - E: Network, Web & Security
Authors: Dr. P. Prabhakar, S. Nageswara Rao (PhD/Dr. count: 1)
View Count (all-time): 258
Total Views (Real + Logic): 10398
Total Downloads (simulated): 2647
Publish Date: 2012 10, Sat
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Typically a user desires to obtain the value of some aggregation function over distributed data items. We present a low-cost, scalable technique to answer continuous aggregation queries using a network of aggregators of dynamic data items. In such a network of data aggregators, each data aggregator serves a set of data items at specific coherencies. Our technique involves decomposing a client query into sub-queries and executing sub-queries on judiciously chosen data aggregators with their individual sub-query incoherency bounds. We provide a technique for getting the optimal set of sub-queries with their incoherency bounds, which satisfies client query’s coherency requirement with least number of refresh messages sent from aggregators to the client. For estimating the number of refresh messages, we build a query cost model which can be used to estimate the number of messages required to satisfy the client specified incoherency bound. Performance results using real-world traces show that our cost based query planning leads to queries being executed using less than one third the number of messages required by existing schemes.
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