Technology, Modeling and Performance
Buch, Englisch, 212 Seiten, Format (B × H): 215 mm x 285 mm, Gewicht: 821 g
ISBN: 978-3-030-36703-9
Verlag: Springer International Publishing
This revised textbook, intended for use in undergraduate/graduate courses on computer networking, computer systems/architecture and performance evaluation, presents a host of new and revised content and ancillaries. This text presents a balanced approach between technology and mathematical modeling. It covers networking algorithms (routing, error codes, protocol verification, line codes, network coding and quantum encryption) and analysis (probability for networking with technological examples, queueing models, divisible load scheduling theory and Amdahl’s Law). There is also a tutorial chapter providing insights into machine learning for networking, the cutting edge of networking technology.
This self-contained text progresses systematically and gives students numerous examples at the end of each chapter. Students in electrical engineering, computer engineering and computer science departments will benefit from this book as will engineers and computer scientists workingin relevant fields.
- Maintains a balanced approach between technology and mathematical modeling
- Features new and revised content covering the latest advances in the field since the original publication
- Includes a host of classroom material for students and instructors
Zielgruppe
Graduate
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung
- Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik
- Mathematik | Informatik EDV | Informatik Technische Informatik Hardware: Grundlagen und Allgemeines
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
Weitere Infos & Material
Introduction.- A Tour through Networking and Computing.- Fundamental Stochastic Models.- Queueing Models.- Fundamental Deterministic Algorithms.- Divisible Load Modeling for Grids.- Amdahl’s and Related Laws.- Machine Learning for Networking.- Conclusion.