Data Streams
Subtitle: Algorithms and Applications
Publisher: Now Publishers; NetLibrary, Incorporated [Distributor]
Published: 2005
Place of publication: Hanover; Boulder
Language: eng
Format: [electronic resource]:
ISBN-13: 9781933019604
Subjects: Missing observations (Statistics); Mathematics; Algorithms; Computable functions; Computer science
Description: In the data stream scenario, input arrives very rapidly and there is limited memory to store the input. Algorithms have to work with one or few passes over the data, space less than linear in the input size or time significantly less than the input size. In the past few years, a new theory has emerged for reasoning about algorithms that work within these constraints on space, time, and number of passes. Some of the methods rely on metric embeddings, pseudo-random computations, sparse approximation theory and communication complexity. The applications for this scenario include IP network traffic analysis, mining text message streams and processing massive data sets in general. Researchers in Theoretical Computer Science, Databases, IP Networking and Computer Systems are working on the data stream challenges. This article is an overview and survey of data stream algorithmics.
Notes: License restrictions may limit access.
Table of contents: title: Abstract; title: 1. Introduction; title: 2. Map; title: 3. The data stream phenomenon; title: 4. Data streaming : formal aspects; title: 5. Foundations : basic mathematical ideas; title: 6. Foundations : basic algorithmic techniques; title: 7. Foundations : summary; title: 8. Streaming systems; title: 9. New directions; title: 10. Historic notes; title: 11. Concluding remarks; title: Acknowledgements; title: References.