Stream Data Processing: A Quality of Service Perspective : Modeling, Scheduling, Load Shedding, and Complex Event Processing / by Qingchun Jiang, Sharma Chakravarthy.

Springer eBooks

OVERVIEW OF DATA STREAM PROCESSING -- DSMS CHALLENGES -- LITERATURE REVIEW -- MODELING CONTINUOUS QUERIES OVER DATA STREAMS -- SCHEDULING STRATEGIES FOR CQs -- LOAD SHEDDING IN DATA STREAM MANAGEMENT SYSTEMS -- NFMi: AN INTER-DOMAIN NETWORK FAULT MANAGEMENT SYSTEM -- INTEGRATING STREAM AND COMPLEX EVENT PROCESSING -- MavStream: DEVELOPMENT OF A DSMS PROTOTYPE -- INTEGRATING CEP WITH A DSMS -- CONCLUSIONS AND FUTURE DIRECTIONS.

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.

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