Data Stream Management

Part I: Introduction.- Part II: Computation of Basic Stream Synopses.- Part III: Mining Data Streams.- Part IV: Advanced Topics.- Part V: Systems and Architectures.- Part VI: Applications.     

Minos Garofalakis is a Professor of Computer Science at the School of Electronic & Computer Engineering of the Technical University of Crete, and the Director of the Software Technology and Network Applications Lab (SoftNet). Previously, he worked as a Member of Technical Staff at Bell Labs, Lucent Technologies (1998-2005), as a Senior Researcher at Intel Research Berkeley (2005-2007), and as a Principal Research Scientist at Yahoo! Research (2007-2008). In parallel, he also held an Adjunct Associate Professor position at the EECS Department of the University of California, Berkeley (2006-2008). Minos's research interests include database systems, centralized/distributed data streams, data synopses and approximate query processing, uncertain databases, and big-data analytics and mining. He has published over 140 scientific papers in top-tier international conferences and journals in these areas. His work has resulted in 36 US Patent filings (29 patents issued) for companies such as Lucent, Yahoo!, and AT&T. Minos is an ACM Distinguished Scientist (2011), and a recipient of the Bell Labs President's Gold Award (2004) and a Marie-Curie International Reintegration Fellowship (2010).

Johannes Gehrke is a Distinguished Engineer at Microsoft working as an architect and product visionary in the Applications and Services Group. From 1999 to 2015 he was the Tisch University Professor in the Department of Computer Science at Cornell University. Johannes' research interests are in the areas of database systems, data science, and data privacy. Johannes has received a National Science Foundation Career Award, an Arthur P. Sloan Fellowship, an IBM Faculty Award, the Cornell College of Engineering James and Mary Tien Excellence in Teaching Award, the Cornell University Provost's Award for Distinguished Scholarship, a Humboldt Research Award from the Alexander von Humboldt Foundation, the 2011 IEEE Computer Society Technical Achievement Award, and

"This impressive volume ... covers both the theory and algorithms related to processing high-speed data streams. ... this is a very useful and well-written text that can be recommended for students, practitioners, and researchers alike. The subject matter fills in a range of details, starting from the basics (including related mathematical theorems) and progressing to describe recent developments along with adequate references to the existing literature and suggestions for future research." (Paparao Kavalipati, Computing Reviews, January, 2017)