Analysis of Fork-Join Systems

Network of Queues with Precedence Constraints
1. Auflage 2022
ISBN: 978-0-367-71263-1
Verlag: Taylor & Francis Ltd

Buch, Englisch, 104 Seiten, Format (B × H): 223 mm x 144 mm, Gewicht: 234 g

Reihe: Emerging Operations Research Methodologies and Applications

With the boom of big data and machine learning and the subsequent need for parallel processing technologies, fork-join queues are more relevant now than ever before. In this book, new estimates of the average response time in fork-join queues are proposed, which form the basis for new research opportunities.

Analysis of Fork-Join Systems: Network of Queues with Precedence Constraints explores numerical approaches to estimate the average response time of fork-join queueing networks and offers never before published simple expressions for the mean response time as conjectures. Extensive experiments are included to demonstrate the remarkable accuracy of the conjectures and algorithms used in the estimation of the average response time.

Graduate students, professors, and researchers in the fields of operations research, management science, industrial engineering, computer science, and electrical engineering will find this book very useful. Students, as well as researchers in both academia and industry, will also find this book of great help when looking for results related to fork-join queues

Autoren/Hrsg.

Sethuraman, Samyukta (Amazon.com)

Sethuraman, Samyukta

Fachgebiete

• Technische Wissenschaften Maschinenbau | Werkstoffkunde Produktionstechnik Fertigungstechnik
• Technische Wissenschaften Technik Allgemein Industrial Engineering
• Mathematik | Informatik Mathematik Stochastik Bayesianische Inferenz
• Mathematik | Informatik Mathematik Operations Research
• Wirtschaftswissenschaften Betriebswirtschaft Unternehmensforschung

Inhaltsverzeichnis

I. INTRODUCTION TO FORK-JOIN QUEUES. II. REVIEW OF LITERATURE ON FORK-JOIN QUEUES. III. SYMMETRIC n-DIMENSIONAL FORK-JOIN QUEUES. IV. COMPLEX FORK-JOIN QUEUEING NETWORKS.

Über Autor(innen)

Samyukta Sethuraman is a Senior Research Scientist at Amazon. Her areas of expertise include queueing systems and pricing and yield management. Samyukta holds a Doctorate in Industrial Engineering from Texas A&M University and a Bachelors from Indian Institute of Technology (IIT) Madras. She serves on the advisory council of the Industrial & Systems Engineering Department at Texas A&M University. One of the focus areas of her doctoral thesis was fork-join queueing systems, which formed the basis of this work.