Formerly CIP. Uk

Includes bibliographical references (pages 340-348) and index.

• Machine generated contents note: 1.Introduction
• I.Network architecture and algorithms
• 2.Mathematics of Internet architecture
• 2.1.Mathematical background: convex optimization
• 2.1.1.Convex sets and convex functions
• 2.1.2.Convex optimization
• 2.2.Resource allocation as utility maximization
• 2.2.1.Utility functions and fairness
• 2.3.Mathematical background: stability of dynamical systems
• 2.4.Distributed algorithms: primal solution
• 2.4.1.Congestion feedback and distributed implementation
• 2.5.Distributed algorithms: dual solution
• 2.6.Feedback delay and stability
• 2.6.1.Linearization
• 2.7.Game-theoretic view of utility maximization
• 2.7.1.The Vickrey
• Clarke
• Groves mechanism
• 2.7.2.The price-taking assumption
• 2.7.3.Strategic or price-anticipating users
• 2.8.Summary
• 2.9.Exercises
• 2.10.Notes
• 3.Links: statistical multiplexing and queues
• 3.1.Mathematical background: the Chernoff bound
• Contents note continued: 3.2.Statistical multiplexing and packet buffering
• 3.2.1.Queue overflow
• 3.3.Mathematical background: discrete-time Markov chains
• 3.4.Delay and packet loss analysis in queues
• 3.4.1.Littl's law
• 3.4.2.The Geo/Geo/1 queue
• 3.4.3.The Geo/Geo/1/B queue
• 3.4.4.The discrete-time G/G/1 queue
• 3.5.Providing priorities: fair queueing
• 3.5.1.Key properties
• 3.6.Summary
• 3.7.Exercises
• 3.8.Notes
• 4.Scheduling in packet switches
• 4.1.Switch architectures and crossbar switches
• 4.1.1.Head-of-line blocking and virtual output queues
• 4.2.Capacity region and MaxWeight scheduling
• 4.2.1.Intuition behind the MaxWeight algorithm
• 4.3.Low-complexity switch scheduling algorithms
• 4.3.1.Maximal matching scheduling
• 4.3.2.Pick-and-compare scheduling
• 4.3.3.Load-balanced switches
• 4.4.Summary
• 4.5.Exercises
• 4.6.Notes
• 5.Scheduling in wireless networks
• 5.1.Wireless communications
• Contents note continued: 5.2.Channel-aware scheduling in cellular networks
• 5.3.The MaxWeight algorithm for the cellular downlink
• 5.4.MaxWeight scheduling for ad hoc P2P wireless networks
• 5.5.General MaxWeight algorithms
• 5.6.Q-CSMA: a distributed algorithm for ad hoc P2P networks
• 5.6.1.The idea behind Q-CSMA
• 5.6.2.Q-CSMA
• 5.7.Summary
• 5.8.Exercises
• 5.9.Notes
• 6.Back to network utility maximization
• 6.1.Joint formulation of the transport, network, and MAC problems
• 6.2.Stability and convergence: a cellular network example
• 6.3.Ad hoc P2P wireless networks
• 6.4.Internet versus wireless formulations: an example
• 6.5.Summary
• 6.6.Exercises
• 6.7.Notes
• 7.Network protocols
• 7.1.Adaptive window flow control and TCP protocols
• 7.1.1.TCP-Reno: a loss-based algorithm
• 7.1.2.TCP-Reno with feedback delay
• 7.1.3.TCP-Vegas: a delay-based algorithm
• 7.2.Routing algorithms: Dijkstra and Bellman-Ford algorithms
• Contents note continued: 7.2.1.Dijkstra's algorithm: link-state routing
• 7.2.2.Bellman-Ford algorithm: distance-vector routing
• 7.3.IP addressing and routing in the Internet
• 7.3.1.IP addressing
• 7.3.2.Hierarchical routing
• 7.4.MAC layer protocols in wireless networks
• 7.4.1.Proportionally fair scheduler in cellular downlink
• 7.4.2.MAC for WiFi and ad hoc networks
• 7.5.Summary
• 7.6.Exercises
• 7.7.Notes
• 8.Peer-to-peer networks
• 8.1.Distributed hash tables
• 8.1.1.Chord
• 8.1.2.Kademlia
• 8.2.P2P file sharing
• 8.2.1.The BitTorrent protocol
• 8.3.Structured P2P streaming
• 8.4.Unstructured P2P streaming
• 8.5.The gossip process
• 8.6.Summary
• 8.7.Exercises
• 8.8.Notes
• II.Performance analysis
• 9.Queueing theory in continuous time
• 9.1.Mathematical background: continuous-time Markov chains
• 9.2.Queueing systems: introduction and definitions
• 9.3.The M/M/1 queue
• 9.4.The M/M/s/s queue
• Contents note continued: 9.4.1.The PASTA property and blocking probability
• 9.5.The M/M/s queue
• 9.6.The M/GI/1 Queue
• 9.6.1.Mean queue length and waiting time
• 9.6.2.Different approaches taken to derive the P-K formula
• 9.7.The GI/GI/1 queue
• 9.8.Reversibility
• 9.8.1.The M/M/1 queue
• 9.8.2.The tandem M/M/1 queue
• 9.9.Queueing systems with product-form steady-state distributions
• 9.9.1.The Jackson network
• 9.9.2.The multi-class M/M/1 queue
• 9.10.Insensitivity to service-time distributions
• 9.10.1.The M/M/1-PS queue
• 9.10.2.The M/GI/1-PS queue
• 9.11.Connection-level arrivals and departures in the internet
• 9.12.Distributed admission control
• 9.13.Loss networks
• 9.13.1.Large-system limit
• 9.13.2.Computing the blocking probabilities
• 9.13.3.Alternative routing
• 9.14.Download time in BitTorrent
• 9.15.Summary
• 9.16.Exercises
• 9.17.Notes
• 10.Asymptotic analysis of queues
• 10.1.Heavy-traffic analysis of the discrete-time G/G/1 queue
• Contents note continued: 10.2.Heavy-traffic optimality of JSQ
• 10.3.Large deviations of i.i.d. random variables: the Cramer
• Chernoff theorem
• 10.4.Large-buffer large deviations
• 10.5.Many-sources large deviations
• 10.6.Summary
• 10.7.Exercises
• 10.8.Notes
• 11.Geometric random graph models of wireless networks
• 11.1.Mathematical background: the Hoeffding bound
• 11.2.Nodes arbitrarily distributed in a unit square
• 11.3.Random node placement
• 11.4.Summary
• 11.5.Exercises
• 11.6.Notes.

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.