Hard Real-Time Computing Systems: Predictable Scheduling Algorithms and Applications - Hardcover

Über die Autorin bzw. den Autor

Giorgio Buttazzo is Full Professor of Computer Engineering at the Scuola Superiore Sant'Anna of Pisa. He graduated in Electronic Engineering at the University of Pisa in 1985, received a Master in Computer Science at the University of Pennsylvania in 1987, and a Ph.D. in Computer Engineering at the Scuola Superiore Sant'Anna of Pisa in 1991. From 1987 to 1988, he worked on active perception and real-time control at the G.R.A.S.P. Laboratory of the University of Pennsylvania, Philadelphia. From 1991 to 1998, he held a position of Assistant Professor at the Scuola Superiore Sant'Anna of Pisa, where he founded and directed the RETIS Laboratory, one of the world leading research groups on real-time systems. From 1998 to 2005 he was Associate Professor at the University of Pavia, directing the Robotics Laboratory at the Computer Science department. In 2003 he co-founded Evidence s.r.l., a spin-off company of the Scuola Superiore Sant'Anna, providing software solutions for real-time embeddedsystems. He has been Chair of the IEEE Technical Committee on Real-Time Systems (2010-2012) and Program Chair and General Chair of the major international conferences on real-time computing. He is IEEE Fellow since 2012 "for contributions to dynamic scheduling algorithms in real-time systems". In 2013 he received the Outstanding Technical Contributions and Leadership Award from the IEEE Technical Committee on Real-Time Systems. He has been Editor-in-Chief of the Journal of Real-Time Systems (Springer), the major journal on real-time computing, and Associate Editor of the IEEE Transactions on Industrial Informatics and the ACM Transactions on Cyber-Physical Systems. He has authored six book editions on real-time systems and over 300 papers in the field of real-time systems, robotics, and neural networks, receiving 13 Best Paper Awards.

Von der hinteren Coverseite

Hard Real-Time Computing Systems is written for instructional use and is organized to enable readers without a strong knowledge of the subject matter to quickly grasp the material. Technical concepts are clearly defined at the beginning of each chapter, and algorithm descriptions are corroborated through concrete examples, illustrations, and tables.  This new, fourth edition includes new sections to explain the variable-rate task model, how to improve predictability and safety in cyber-physical real-time systems that exploit machine learning algorithms, additional coverage on Response Time Analysis, and a new chapter on implementing periodic real-time tasks under Linux.