Eddies: continuously adaptive query processing
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OSDI '02 Proceedings of the 5th symposium on Operating systems design and implementationCopyright restrictions prevent ACM from being able to make the PDFs for this conference available for downloading
Cost-efficient processing of MIN/MAX queries over distributed sensors with uncertainty
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Energy-efficient monitoring of extreme values in sensor networks
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
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VLDB '06 Proceedings of the 32nd international conference on Very large data bases
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WISE'06 Proceedings of the 7th international conference on Web Information Systems
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We address the problem of cost-efficient processing of continuous extreme queires (MAX or MIN) over distributed sliding window streams, and propose several methods for communication reduction and resource sharing among queries. Firstly, we develop an effective pruning technique to minimize the number of elements to be kept. It can be shown that on average only O(logN) key points need to be stored for exact answer of extreme query, where N is the number of points contained in the sliding window. Then we consider the distributed environment, where remote nodes delay the data transmission as late as possible, and adopt the pruning strategy to filter local stream tuples, which is quite efficient in communication reduction. Analytical analysis and experimental evidences show the efficiency of proposed approach both on storage/communication reduction and efficiency improvement.