TY  - BOOK
AU  - Chaudhry,Nauman A.
AU  - Shaw,Kevin
AU  - Abdelguerfi,Mahdi
ED  - SpringerLink (Online service)
TI  - Stream Data Management
T2  - Advances in Database Systems,
SN  - 9780387252292
AV  - QA76.9.D3 
U1  - 005.74 23
PY  - 2005///
CY  - Boston, MA
PB  - Springer US
KW  - Computer science
KW  - Computer Communication Networks
KW  - Database management
KW  - Information storage and retrieval systems
KW  - Information systems
KW  - Multimedia systems
KW  - Computer Science
KW  - Database Management
KW  - Information Storage and Retrieval
KW  - Multimedia Information Systems
KW  - Models and Principles
KW  - Information Systems Applications (incl.Internet)
N1  - to Stream Data Management -- Query Execution and Optimization -- Filtering, Punctuation, Windows and Synopses -- XML & Data Streams -- CAPE: A Constraint-Aware Adaptive Stream Processing Engine -- Efficient Support for Time Series Queries in Data Stream Management Systems -- Managing Distributed Geographical Data Streams with the GIDB Portal System -- Streaming Data Dissemination Using Peer-Peer Systems
N2  - Researchers in data management have recently recognized the importance of a new class of data-intensive applications that requires managing data streams, i.e., data composed of continuous, real-time sequence of items. Streaming applications pose new and interesting challenges for data management systems. Such application domains require queries to be evaluated continuously as opposed to the one time evaluation of a query for traditional applications. Streaming data sets grow continuously and queries must be evaluated on such unbounded data sets. These, as well as other challenges, require a major rethink of almost all aspects of traditional database management systems to support streaming applications. Stream Data Management comprises eight invited chapters by researchers active in stream data management. The collected chapters provide exposition of algorithms, languages, as well as systems proposed and implemented for managing streaming data. Stream Data Management is designed to appeal to researchers or practitioners already involved in stream data management, as well as to those starting out in this area. This book is also suitable for graduate students in computer science interested in learning about stream data management.
UR  - http://dx.doi.org/10.1007/b106968
ER  -