
AIMD Dynamics and Distributed Resource Allocation
Society for Industrial & Applied Mathematics,U.S. (Publisher)
Published on 28. February 2016
Book
Paperback/Softback
249 pages
978-1-61197-421-8 (ISBN)
Description
This is the first comprehensive book on the AIMD algorithm, the most widely used method for allocating a limited resource among competing agents without centralized control. The authors offer a new approach that is based on positive switched linear systems. It is used to develop most of the main results found in the book, and fundamental results on stochastic switched nonnegative and consensus systems are derived to obtain these results.
The original and best known application of the algorithm is in the context of congestion control and resource allocation on the Internet, and readers will find details of several variants of the algorithm in order of increasing complexity, including deterministic, random, linear, and nonlinear versions. In each case, stability and convergence results are derived based on unifying principles. Basic and fundamental properties of the algorithm are described, examples are used to illustrate the richness of the resulting dynamical systems, and applications are provided to show how the algorithm can be used in the context of smart cities, intelligent transportation systems, and the smart grid.
The original and best known application of the algorithm is in the context of congestion control and resource allocation on the Internet, and readers will find details of several variants of the algorithm in order of increasing complexity, including deterministic, random, linear, and nonlinear versions. In each case, stability and convergence results are derived based on unifying principles. Basic and fundamental properties of the algorithm are described, examples are used to illustrate the richness of the resulting dynamical systems, and applications are provided to show how the algorithm can be used in the context of smart cities, intelligent transportation systems, and the smart grid.
More details
Series
Language
English
Place of publication
New York
United States
Target group
Professional and scholarly
Product notice
Paperback (trade)
Unsewn / adhesive bound
Dimensions
Height: 253 mm
Width: 177 mm
Thickness: 13 mm
Weight
472 gr
ISBN-13
978-1-61197-421-8 (9781611974218)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
M. Corless is a Professor in the School of Aeronautics and Astronautics at Purdue University, a Visiting Professor at University College Dublin, and an Adjunct Honorary Professor at the National University of Ireland, Maynooth. He has held a visiting position at IBM Research Ireland and is the recipient of an NSF Presidential Young Investigator Award. His research is concerned with obtaining tools that are useful in the robust analysis and control of systems containing significant uncertainty, and in applying these tools in a variety of situations. C. King is a Professor in the Mathematics Department at Northeastern University. He previously held positions at Princeton and Cornell Universities and visiting positions at ETH Zurich, Microsoft Research, and the Hamilton Institute at the National University of Ireland, Maynooth. He is a Fellow of the American Mathematical Society. His research interests include dynamical systems, quantum information theory, and mathematical physics. R. Shorten is a Professor of Control Engineering and Decision Science at University College Dublin. He is a co-founder of, and former Professor at, the Hamilton Institute at the National University of Ireland, Maynooth. He has also held a Visiting Professor position at TU Berlin, and a Senior Manager position at IBM Research Ireland, where he led the Control and Optimization activities in the area of Smart Cities. He has been active in computer networking, automotive research, collaborative mobility (including smart transportation and electric vehicles), and basic control theory and linear algebra. His main field of theoretical research is hybrid dynamical systems and stability theory for linear time-varying systems. F. Wirth is the Chair for Dynamical Systems at the University of Passau. He has held positions at the Centre Automatique et Systemes at Ecole des Mines de Paris, the University of Bremen, the University of Frankfurt, the University of Wuerzburg, the Hamilton Institute at the National University of Ireland, Maynooth, and IBM Research Ireland. He is interested in the various guises of stability properties of dynamical systems and their applications.
Content
Chapter 1: Origins and Applications of AIMD
Part I: Linear AIMD
Chapter 2: Synchronized Homogeneous AIMD
Chapter 3: Nonsynchronized Nonhomogeneous AIMD
Chapter 4: The IID AIMD Model
Chapter 5: Mathematical Background for Part I
Part II: Stochastic Linear AIMD;Chapter 6: IID AIMD and Ergodicity
Chapter 7: AIMD with State-Dependent Transition Probabilities
Chapter 8: A Markov Chain Model for Capacity Events
Chapter 9: Mathematical Background for Part II
Part III: Nonlinear AIMD
Chapter 10: A Primer on Nonlinear AIMD
Chapter 11: Synchronized Homogeneous Nonlinear AIMD
Chapter 12: Nonsynchronized Nonhomogeneous NAIMD
Chapter 13: Nonsynchronized Algorithms with Stochastic State-Dependent Growth Rates
Part IV: Applications of AIMD Algorithms
Chapter 14: Three Sample Applications of AIMD
Chapter 15: Another Application: Network Utility Optimization
Chapter 16: Mathematical Background for Part IV
Bibliography
Index.
Part I: Linear AIMD
Chapter 2: Synchronized Homogeneous AIMD
Chapter 3: Nonsynchronized Nonhomogeneous AIMD
Chapter 4: The IID AIMD Model
Chapter 5: Mathematical Background for Part I
Part II: Stochastic Linear AIMD;Chapter 6: IID AIMD and Ergodicity
Chapter 7: AIMD with State-Dependent Transition Probabilities
Chapter 8: A Markov Chain Model for Capacity Events
Chapter 9: Mathematical Background for Part II
Part III: Nonlinear AIMD
Chapter 10: A Primer on Nonlinear AIMD
Chapter 11: Synchronized Homogeneous Nonlinear AIMD
Chapter 12: Nonsynchronized Nonhomogeneous NAIMD
Chapter 13: Nonsynchronized Algorithms with Stochastic State-Dependent Growth Rates
Part IV: Applications of AIMD Algorithms
Chapter 14: Three Sample Applications of AIMD
Chapter 15: Another Application: Network Utility Optimization
Chapter 16: Mathematical Background for Part IV
Bibliography
Index.