Module Specifications.
Current Academic Year 2024 - 2025
All Module information is indicative, and this portal is an interim interface pending the full upgrade of Coursebuilder and subsequent integration to the new DCU Student Information System (DCU Key).
As such, this is a point in time view of data which will be refreshed periodically. Some fields/data may not yet be available pending the completion of the full Coursebuilder upgrade and integration project. We will post status updates as they become available. Thank you for your patience and understanding.
Date posted: September 2024
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Description The ability to predict how a data communications network will perform in terms of delay, throughput or packet loss is an important aspect of the engineering practice of computer and telecommunications network design. Given the complexity of operation of communications protocols, coupled with the randomness of data traffic transported by a network, gaining a reliable estimate of system performance requires careful analysis with appropriate modelling techniques. The aim of this module is to firstly review the operating principles of data communications protocols and then to develop the basic theory and practice required for evaluating the performance of communications systems and data networks, using discrete-state mathematical and computer simulation modelling methods. | |||||||||||||||||||||||||||||||||||||||||||
Learning Outcomes 1. Describe the basic operating principles of the protocols used to implement various layers of the OSI model and identify their basic performance parameters, 2. design and implement a disrcete-event computer simulation model for performance evaluation of a data communications network and be able to analyse the simulation output using statistical methods, 3. derive results relating to single server queuing models and networks of queues, 4. apply the analytic techniques of probability and queuing theory to calculate the performance characteristics of selected communications systems or protocols, 5. compare the achievable accuracy of the results from simulation models to that of analytic models that employ approximations to achieve a tractable solution. | |||||||||||||||||||||||||||||||||||||||||||
All module information is indicative and subject to change. For further information,students are advised to refer to the University's Marks and Standards and Programme Specific Regulations at: http://www.dcu.ie/registry/examinations/index.shtml |
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Indicative Content and Learning Activities
Review of Data Network Protocols and Introduction to Performance EvaluationNetwork layer functions and an intrduction to circuit and packet switching, link layer protocols, IP, routing, TCP, and application protocols. Future network trends. Motivation for the use of analysis and simulation methods: performance measures, resource allocation/dimensioning, deployment costs.Mathematical Fundamentals for Performance AnalysisProbability spaces, probability functions, random variables, probability laws, stochastic processes, renewal processes, Poisson process, Markov processes and Birth-Death processes.Discrete-Event Stochastic Simulation MethodsIntroduction to simulation modelling methodologies, random variates, pseudo-random number generators, non-uniform variates: inverse transform sampling and rejection sampling, event-lists, event scheduling and implementation, simulation validation, confidence intervals, and analysis of results.Queueing Analysis MethodsPerformance measures and objectives, Kendall's notation, Little's law, Markovian queueing systems, M/M/1, M/M/infinity, M/M/n, M/M/1/K, M/M/m/m, priority queues, the M/G/1 and M/D/1 queue. Product-Form Queueing networks.Analysis of Network Protocol PerformanceExamples such as LAN/MAN random access and polling networks, packet switched network throughput, and router queue management. | |||||||||||||||||||||||||||||||||||||||||||
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Indicative Reading List
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