Stream Data Processing: A Quality of Service Perspective

Data Stream Management Systems (DSMSs) are the systems used to process data streams and provide for the needs of stream-based applications. This book presents a new paradigm to meet the needs of these applications, including a detailed discussion of the techniques proposed. It includes important aspects of a QoS-driven DSMS (Data Stream Management System) and introduces applications where a DSMS can be used and discusses needs beyond the stream processing model. It also discusses in detail the design and implementation of MavStream. This volume is primarily intended as a reference book for researchers and advanced-level students in computer science. It is also appropriate for practitioners in industry who are interested in developing applications.

Includes important aspects of a QoS-driven DSMS (Data Stream Management System) Introduces applications where a DSMS can be used and discusses needs beyond the stream processing model Discusses in detail the design and implementation of MavStream

Texte du rabat

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.

Contenu
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.