Analyzing the Query Performance over a Distributed Network of Data Aggregators
Keywords:
Content distribution network, continuous query, online decision making, data dissemination, coherency, performance
Abstract
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 subquery incoherency bounds. We provide a technique for getting the optimal set of sub-queries with their incoherency bounds, which satisfies client query2019;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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Published
2012-03-15
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Copyright (c) 2012 Authors and Global Journals Private Limited
This work is licensed under a Creative Commons Attribution 4.0 International License.