Overview

The course systematically develops the traffic characteristics of DoD and commercial broadband services (video, voice, text, and other multimedia information) and determines the need for high-speed networks with emphasis on quality of service. Queuing theory is used in the design and analysis of the various modules of a high-speed network: traffic modeling, switches, admission control, scheduling, traffic monitoring, and congestion control. Emerging trends and technologies that enable deployment of high-speed global networks for tactical, commercial, and residential use are discussed. Topics include queuing theory, traffic models, traffic management, and broadband technologies, such as ATM, Gigabit Ethernet, DSL, and cable access. Laboratory is concerned with the use of OPNET for simulation studies of various network topologies.

Included in Degrees & Certificates

• 295

Prerequisites

• EC3710
• CS3502
• Or consent of instructor

Learning Outcomes

• The student will be able to list the data rates of various multimedia information (speech, audio, image, video, and text) and determine the required transport channel capacities.
• Given a description of the multimedia information, the student will be able to determine the appropriate adaptation layer protocol.
• Given the number of users and their average source data rates, the student will be able to determine the protocol efficiency and estimate the required channel capacity.
• Given the application scenario, the student will be able to propose an access technology.
• Given the state transition rates and traffic arrival statistics, the student will be able to analyze the queuing scheme (M/M/1, M/D/1, D/D/1) and determine the overload and underload states.
• Given the voice activity factor and transition rates, the student will be able to develop a Markov model multiple voice sources and determine the buffer capacity requirements for the switch.
• Given the traffic characteristics of variable bit rate real-time information, the student will be able to determine the admission control laws based on peak, average or Gaussian rules.
• Given the traffic generation characteristics of a source, the student will be able to determine the rate control parameters and buffer occupancy profile under network congestion.