Network Optimization and Control is the ideal starting point for a mature reader with little background on the subject of congestion control to understand the basic concepts underlying network resource allocation.

Linear Network Optimization presents a thorough treatment of classical approaches to network problems such as shortest path, max-flow, assignment, transportation, and minimum cost flow problems.

This book constitutes the refereed proceedings of the Second Euro-NF International Conference, NET-COOP 2008 held in Paris, France, in September 2008. The 13 revised full papers presented were carefully reviewed and selected from a total of 27 submissions. The papers are organized in topical sections on economics and peer-to-peer networks; routing and measurements; scheduling; tcp and congestion control; as well as wireless networks.

This book constitutes the refereed proceedings of the First Euro-FGI International Conference on Network Control and Optimization, NET-COOP 2007, held in Avignon, France in June 2007. The 22 revised full papers presented together with nine invited lectures address all current issues in network control and optimization, ranging from performance evaluation and optimization of general stochastic networks to more specific targets.

This text presents a modern theory of analysis, control, and optimization for dynamic networks. Mathematical techniques of Lyapunov drift and Lyapunov optimization are developed and shown to enable constrained optimization of time averages in general stochastic systems. The focus is on communication and queueing systems, including wireless networks with time-varying channels, mobility, and randomly arriving traffic. A simple drift-plus-penalty framework is used to optimize time averages such as throughput, throughput-utility, power, and distortion. Explicit performance-delay tradeoffs are provided to illustrate the cost of approaching optimality. This theory is also applicable to problems in operations research and economics, where energy-efficient and profit-maximizing decisions must be made without knowing the future. Topics in the text include the following: - Queue stability theory - Backpressure, max-weight, and virtual queue methods - Primal-dual methods for non-convex stochastic utility maximization - Universal scheduling theory for arbitrary sample paths - Approximate and randomized scheduling theory - Optimization of renewal systems and Markov decision systems Detailed examples and numerous problem set questions are provided to reinforce the main concepts. Table of Contents: Introduction / Introduction to Queues / Dynamic Scheduling Example / Optimizing Time Averages / Optimizing Functions of Time Averages / Approximate Scheduling / Optimization of Renewal Systems / Conclusions

A modern mathematical approach to the design of communication networks for graduate students, blending control, optimization, and stochastic network theories alongside a broad range of performance analysis tools. Practical applications are illustrated by making connections to network algorithms and protocols. End-of-chapter problems covering a range of difficulties support student learning.

Network optimization is important in the modeling of problems and processes from such fields as engineering, computer science, operations research, transportation, telecommunication, decision support systems, manufacturing, and airline scheduling. Recent advances in data structures, computer technology, and algorithm development have made it possible to solve classes of network optimization problems that until recently were intractable. The refereed papers in this volume reflect the interdisciplinary efforts of a large group of scientists from academia and industry to model and solve complicated large-scale network optimization problems.

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).

During the period April 25th to May 10th, 1984 the 3rd Course of the International School of Advanced Geodesy entitled "Optimization and Design of Geodetic Networks" took place in Erice. The main subject of the course is clear from the title and consisted mainly of that particular branch of network analysis, which results from applying general concepts of mathematical optimization to the design of geodetic networks. As al ways when dealing with optimization problems, there is an a-priori choice of the risk (or gain) function which should be minimized (or maximized) according to the specific interest of the "designer", which might be either of a scientific or of an economic nature or even of both. These aspects have been reviewed in an intro ductory lecture in which the particular needs arising in a geodetic context and their analytical representations are examined. Subsequently the main body of the optimization problem, which has been conven tionally divided into zero, first, second and third order design problems, is presented. The zero order design deals with the estimability problem, in other words with the definition of which parameters are estimable from a given set of observa tions. The problem results from the fact that coordinates of points are not univocally determined from the observations of relative quantities such as angles and distances, whence a problem of the optimal choice of a reference system, the so-called "datum problem" arises.

Optimal and Robust Scheduling for Networked Control Systems tackles the problem of integrating system components—controllers, sensors, and actuators—in a networked control system. It is common practice in industry to solve such problems heuristically, because the few theoretical results available are not comprehensive and cannot be readily applied by practitioners. This book offers a solution to the deterministic scheduling problem that is based on rigorous control theoretical tools but also addresses practical implementation issues. Helping to bridge the gap between control theory and computer science, it suggests that the consideration of communication constraints at the design stage will significantly improve the performance of the control system. Technical Results, Design Techniques, and Practical Applications The book brings together well-known measures for robust performance as well as fast stochastic algorithms to assist designers in selecting the best network configuration and guaranteeing the speed of offline optimization. The authors propose a unifying framework for modelling NCSs with time-triggered communication and present technical results. They also introduce design techniques, including for the codesign of a controller and communication sequence and for the robust design of a communication sequence for a given controller. Case studies explore the use of the FlexRay TDMA and time-triggered control area network (CAN) protocols in an automotive control system. Practical Solutions to Your Time-Triggered Communication Problems This unique book develops ready-to-use engineering tools for large-scale control system integration with a focus on robustness and performance. It emphasizes techniques that are directly applicable to time-triggered communication problems in the automotive industry and in avionics, robotics, and automated manufacturing.