Stream Data Processing: A Quality of Service Perspective : Modeling, Scheduling, Load Shedding, and Complex Event Processing

Sharma Chakravarthy

ISBN 10: 0387710027 / ISBN 13: 9780387710020

Editore: Springer Us Mai 2009, 2009

Riguardo questo articolo

Neuware - In recent years, a new class of applications has come to the forefront { p- marily due to the advancement in our ability to collect data from multitudes of devices, and process them e ciently. These include homeland security - plications, sensor/pervasive computing applications, various kinds of mo- toring applications, and even traditional applications belonging to nancial, computer network management, and telecommunication domains. These - plications need to process data continuously (and as long as data is available) from one or more sources. The sequence of data items continuously gen- ated by sources is termed a data stream. Because of the possible never-ending nature of a data stream, the amount of data to be processed is likely to be unbounded. In addition, timely detection of interesting changes or patterns or aggregations over incoming data is critical for many of these applications. Furthermore, the data arrival rates may uctuate over a period of time and may be bursty at times. For most of these applications, Quality of Service (or QoS) requirements, such as response time, memory usage, and throughput are extremely important. These application requirements make it infeasible to simply load the incoming data streams into a persistent store and process them e ectively using currently available database management techniques.

Codice articolo 9780387710020

Dati bibliografici

• Titolo: Stream Data Processing: A Quality of Service Perspective : Modeling, Scheduling, Load Shedding, and Complex Event Processing
• Editore: Springer Us Mai 2009
• Data di pubblicazione: 2009
• Lingua: Inglese
• ISBN 10: 0387710027
• ISBN 13: 9780387710020
• Rilegatura: Buch
• Condizione: Neu
• Dimensioni: 243 L x 161 A x 25 P (millimetri) 243 millimetri di larghezza per 161 millimetri di altezza per 25 millimetri di profondità
• Peso: 619 grammi

Descrizione articolo

Riassunto

In recent years, a new class of applications has come to the forefront { p- marily due to the advancement in our ability to collect data from multitudes of devices, and process them e ciently. These include homeland security - plications, sensor/pervasive computing applications, various kinds of mo- toring applications, and even traditional applications belonging to nancial, computer network management, and telecommunication domains. These - plications need to process data continuously (and as long as data is available) from one or more sources. The sequence of data items continuously gen- ated by sources is termed a data stream. Because of the possible never-ending nature of a data stream, the amount of data to be processed is likely to be unbounded. In addition, timely detection of interesting changes or patterns or aggregations over incoming data is critical for many of these applications. Furthermore, the data arrival rates may uctuate over a period of time and may be bursty at times. For most of these applications, Quality of Service (or QoS) requirements, such as response time, memory usage, and throughput are extremely important. These application requirements make it infeasible to simply load the incoming data streams into a persistent store and process them e ectively using currently available database management techniques.

Dalla quarta di copertina

Traditional database management systems, widely used today, are not well-suited for a class of emerging applications. These applications, such as network management, sensor computing, and so on, need to continuously process large amounts of data coming in the form of a stream and in addition, meet stringent response time requirements.  Support for handling QoS metrics, such as response time, memory usage, and throughput, is central to any system proposed for the above applications.

Stream Data Processing: A Quality of Service Perspective (Modeling,Scheduling, Load Shedding, and Complex Event Processing), presents a new paradigm suitable for stream and complex event processing. This book covers a broad range of topics in stream data processing and includes detailed technical discussions of a number of proposed techniques from QoS perspective.

This volume is intended as a text book for graduate courses and as a reference book for researchers, advanced-level students in computer sciences, and IT practitioners.