Includes bibliographical references and index.

Front Matter -- Introduction -- Modeling. Definitions and Notation -- Performance Metrics in Networks -- Routing Problems -- Capacity Assignment Problems -- Congestion Control Problems -- Topology Design Problems -- Algorithms. Gradient Algorithms in Network Design -- Primal Gradient Algorithms -- Dual Gradient Algorithms -- Decomposition Techniques -- Heuristic Algorithms -- Appendix A: Convex Sets. Convex Functions -- Appendix B: Mathematical Optimization Basics -- Appendix C: Complexity Theory -- Appendix D: Net2Plan -- Index

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. -- Provided by publisher.