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.
<STRONG>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.
Stream Data Processing: A Quality of Service Perspective Modeling, Scheduling, Load Shedding, and Complex Event Processing ADVANCES IN DATABASE SYSTEMS Volume 36 Series Editors Ahmed K. Elmagarmid Amit P. Sheth Purdue University West Lafayette, IN 47907 Wright State University Dayton, Ohio 45435 For other titles published in this series, go to www.springer.com/series/5573 Stream Data Processing: A Quality of Service Perspective Modeling, Scheduling, Load Shedding, and Complex Event Processing by Sharma Chakravarthy The University of Texas at Arlington Arlington, TX, USA Qingchun Jiang Oracle Corporation Redwood Shores, CA, USA Sharma Chakravarthy Department of Computer Science & Engineering University of Texas at Arlington Arlington, TX 76019, USA
[email protected] ISBN: 978-0-387-71002-0 DOI: 10.1007/978-0-387-71003-7 Qingchun Jiang Oracle Corporation 500 Oracle Parkway Redwood Shores, CA 94065, USA
[email protected] e-ISBN: 978-0-387-71003-7 Library of Congress Control Number: 2009920957 © Springer Science+Business Media, LLC 2009 All rights reserved. This work may not be translated or copied in whole or in part without the written permission of the publisher (Springer Science+Business Media, LLC, 233 Spring Street, New York, NY 10013, USA), except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights. Printed on acid-free paper springer.com In Loving Memory of my father Vidwan Chakravarthy Ananthachar (27th June 1916 to 9th December 2000) who instilled in me an appreciation for learning and a thirst for knowledge – Sharma Chakravarthy To my wife Ailing Wang, and kids George and Kevin for their unconditional love and support – Qingchun Jiang Preface In recent years, a new class of applications has come to the forefront – primarily due to the advancement in our ability to collect data from multitudes of devices, and process them efficiently. These include homeland security applications, sensor/pervasive computing applications