Front Matter
 1 Introduction
  1.1 Networks in practice
  1.2 Mathematical models
  1.3 What do you need to know to read this book?
  1.4 Notes
 Part I: Modeling and Control
  2 Examples
   2.1 Modeling the single server queue
   2.2 Klimov model
   2.3 Capacity and queueing in communication systems
   2.4 Multiple-access communication
   2.5 Processor sharing model
   2.6 Inventory model
   2.7 Power transmission network
   2.8 Optimization in a simple re-entrant line
   2.9 Contention for resources and instability
   2.10 Routing model
   2.11 Braess' paradox
   2.12 Notes
  3 The Single Server Queue
   3.1 Representations
   3.2 Approximations
   3.3 Stability
   3.4 Invariance equations
   3.5 Big queues
   3.6 Model selection
   3.7 Notes
   Exercises
  4 Scheduling
   4.1 Controlled random-walk model
   4.2 Fluid model
   4.3 Control techniques for the fluid model
   4.4 Comparing fluid and stochastic models
   4.5 Structure of optimal policies
   4.6 Safety-stocks
   4.7 Discrete review
   4.8 MaxWeight and MinDrift
   4.9 Perturbed value function
   4.10 Notes
   Exercises
 Part II: Workload
  5 Workload and Scheduling
   5.1 Single server queue
   5.2 Workload for the CRW scheduling model
   5.3 Relaxations for the fluid model
   5.4 Stochastic workload models
   5.5 Pathwise optimality and workload
   5.6 Hedging in networks
   5.7 Notes
   Exercises
  6 Routing and Resource Pooling
   6.1 Workload in general models
   6.2 Resource pooling
   6.3 Routing and workload
   6.4 MaxWeight for routing and scheduling
   6.5 Simultaneous resource possession
   6.6 Workload relaxations
   6.7 Relaxations and policy synthesis for stochastic models
   6.8 Notes
   Exercises
  7 Demand
   7.1 Network models
   7.2 Transients
   7.3 Workload relaxations
   7.4 Hedging in a simple inventory model
   7.5 Hedging in networks
   7.6 Summary of steady-state control techniques
   7.7 Notes
   Exercises
 Part III: Stability and Performance
  8 Foster—Lyapunov Techniques
   8.1 Lyapunov functions
   8.2 Lyapunov functions for networks
   8.3 Discrete review
   8.4 MaxWeight
   8.5 MaxWeight and the average-cost optimality equation
   8.6 Linear programs for performance bounds
   8.7 Brownian workload model
   8.8 Notes
   Exercises
  9 Optimization
   9.1 Reachability and decomposibility
   9.2 Linear programming formulations
   9.3 Multiobjective optimization
   9.4 Optimality equations
   9.5 Algorithms
   9.6 Optimization in networks
   9.7 One-dimensional inventory model
   9.8 Hedging and workload
   9.9 Notes
   Exercises
  10 ODE Methods
   10.1 Examples
   10.2 Mathematical preliminaries
   10.3 Fluid limit model
   10.4 Fluid-scale stability
   10.5 Safety stocks and trajectory tracking
   10.6 Fluid-scale asymptotic optimality
   10.7 Brownian workload model
   10.8 Notes
   Exercises
  11 Simulation and Learning
   11.1 Deciding when to stop
   11.2 Asymptotic theory for Markov models
   11.3 The single-server queue
   11.4 Control variates and shadow functions
   11.5 Estimating a value function
   11.6 Notes
 Exercises
 Appendix Markov Models
 Bibliography