Book description
This book covers the design and optimization of computer networks applying a rigorous optimization methodology, applicable to any network technology. It is organized into two parts. In Part 1 the reader will learn how to model network problems appearing in computer networks as optimization programs, and use optimization theory to give insights on them. Four problem types are addressed systematically – traffic routing, capacity dimensioning, congestion control and topology design.
Part 2 targets the design of algorithms that solve network problems like the ones modeled in Part 1. Two main approaches are addressed – gradient-like algorithms inspiring distributed network protocols that dynamically adapt to the network, or cross-layer schemes that coordinate the cooperation among protocols; and those focusing on the design of heuristic algorithms for long term static network design and planning problems.
Following a hands-on approach, the reader will have access to a large set of examples in real-life technologies like IP, wireless and optical networks. Implementations of models and algorithms will be available in the open-source Net2Plan tool from which the user will be able to see how the lessons learned take real form in algorithms, and reuse or execute them to obtain numerical solutions.
An accompanying link to the author’s own Net2plan software enables readers to produce numerical solutions to a multitude of real-life problems in computer networks (www.net2plan.com).
Table of contents
- Title Page
- Copyright
- Dedication
- About the Author
- Preface
- Acknowledgments
- Part One: Modeling
-
Part Two: Algorithms
- Chapter 8: Gradient Algorithms in Network Design
- Chapter 9: Primal Gradient Algorithms
- Chapter 10: Dual Gradient Algorithms
-
Chapter 11: Decomposition Techniques
- 11.1 Introduction
- 11.2 Theoretical Fundamentals
- 11.3 Cross-Layer Congestion Control and QoS Capacity Allocation
- 11.4 Cross-Layer Congestion Control and Backpressure Routing
- 11.5 Cross-Layer Congestion Control and Power Allocation
- 11.6 Multidomain Routing
- 11.7 Dual Decomposition in Non-Convex Problems
- 11.8 Notes and Sources
- 11.9 Exercises
- References
-
Chapter 12: Heuristic Algorithms
- 12.1 Introduction
- 12.2 Heuristic Design Keys
- 12.3 Local Search Algorithms
- 12.4 Simulated Annealing
- 12.5 Tabu Search
- 12.6 Greedy Algorithms
- 12.7 GRASP
- 12.8 Ant Colony Optimization
- 12.9 Evolutionary Algorithms
- 12.10 Case Study: Greenfield Plan with Recovery Schemes Comparison
- 12.11 Notes and Sources
- 12.12 Exercises
- References
- Appendix A: Convex Sets. Convex Functions
- Appendix B: Mathematical Optimization Basics
-
Appendix C: Complexity Theory
- C.1 Introduction
- C.2 Deterministic Machines and Deterministic Algorithms
- C.3 Non-Deterministic Machines and Non-Deterministic Algorithms
- C.4 and Complexity Classes
- C.5 Polynomial Reductions
- C.6 -Completeness
- C.7 Optimization Problems and Approximation Schemes
- C.8 Complexity of Network Design Problems
- C.9 Notes and Sources
- References
- Appendix D: Net2Plan
- End User License Agreement
Product information
- Title: Optimization of Computer Networks
- Author(s):
- Release date: May 2016
- Publisher(s): Wiley
- ISBN: 9781119013358
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