Stream data processing: a quality of service perspective: modeling, scheduling, load shedding, and complex event processing

Traditional database management systems (DBMSs) are widely used in applications that require persistent storage and processing of ad hoc queries to manage and process a large volume of data. A large class of newer applications - in finance, computer network management, telecommunications, homeland security, sensor/pervasive computing, and environmental monitoring - produce data continuously and the data is typically presented in a data stream. The systems used toprocess data streams and provide for the needs of stream-based applications are Data Stream Management Systems (DSMSs). Stream Data Processing: Issues and Solutions presents a new paradigm to meet the needs of these applications, including a detailed discussion of the techniques proposed. This volume is intended as a reference book for researchers and advanced-level students in computerscience. 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). INDICE: Preface.- Introduction.- Stream Data Processing Operators.- StreamData Processing Architecture.- Overview of Stream Processing Systems.- Continuous Query Modeling.- Capacity Modeling.- Scheduling Strategies.- Load Shedding and Admission Control.- DBMS Implementation Issues.- Applications of DBMS.- Beyond DBMS.- Index.

• ISBN: 978-0-387-71002-0
• Editorial: Springer
• Encuadernacion: Cartoné
• Páginas: 324
• Fecha Publicación: 31/12/2009
• Nº Volúmenes: 1
• Idioma: Inglés