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  1. Proceedings of the on SIGMOD/PODS 2012 PhD Symposium (PhD '12)
  2. Efficient optimization and processing for distributed monitoring and control applications
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Efficient optimization and processing for distributed monitoring and control applications

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Efficient optimization and processing for distributed monitoring and control applications

Content Provider ACM Digital Library
Author Liu, Mengmeng
Abstract In recent years, we have seen an increasing number of applications in networking, sensor networks, cloud computing, and environmental monitoring, that aim to monitor, control, and make decisions over large volumes of dynamic data. In my dissertation, we aim to enable a generic framework for these distributed monitoring and control applications, and address the limitations of prior work such as data stream management systems and adaptive query processing systems. In particular, we make the following contributions: 1) supporting the maintenance of recursive queries over distributed data streams, 2) enabling full-fledged cost-based incremental query re-optimization, and 3) as ongoing work, incorporating the cost estimation of plan switching during query re-optimization. Our solutions are implemented and evaluated using our prototype system Aspen, over a variety of workloads and benchmarks. In addition, our prototype system Aspen enables an end-to-end framework to support control and decision-making over integrated data streams from both the physical world (e.g., sensor streams) and the digital world (e.g., web, streams, databases).
Ending Page 74
Page Count 6
Starting Page 69
File Format PDF
ISBN 9781450313261
DOI 10.1145/2213598.2213615
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2012-05-20
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Adaptive Stream Recursive Optimization
Content Type Text
Resource Type Article
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