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Network Design and Optimisation (ELEN90003)

Graduate courseworkPoints: 12.5Not available in 2019

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Year of offerNot available in 2019
Subject levelGraduate coursework
Subject codeELEN90003
FeesSubject EFTSL, Level, Discipline & Census Date


This subject provides knowledge and skills necessary for analysis, design modelling and optimisation of telecommunication networks.


This subject is a collection of analytical, numerical and optimisation techniques relating to network modelling and optimisation.

Topics in this subject can be generically applied to wired or wireless networks and are not limited to any specific type or tier. More specifically, the subject will include:

  • Topological modelling of telecommunication network;
  • Capacity planning and design; problems involving flow;
  • Content and data delivery; supply and demand in telecommunication networks;
  • Network cost optimisation with flow considerations;
  • Collision detection; spanning trees, ethernet and its application;
  • Routing protocols; shortest path problems;
  • Application of evolutionary computation in network design and optimisation (will be presented subject to time availability);
  • Quality of service and class of service (core network); Multiprotocole Label Switching (will be presented subject to time availability);
  • Designing for performance, consideration of service level agreements in network design;
  • Survivability, reliability and availability in network design; Designing fault tolerant network; Self healing design techniques; Fault detection mechanisms;
  • Packet loss, delay and buffer size consideration in network design; Application of relevant queuing models.

Intended learning outcomes


On completion of the subject, students will be equipped with a strong background in application of modelling and analytical techniques to design and optimise networking problems. Specifically, it is expected that students acquire the following set of skills and knowledge:

  1. Linear programming formulation of network design and optimisation problem; Simplex algorithm
  2. Maximum flow problem; Path augmentation and labelling methods Transportation problem; Minimum cost and penalty cost method for finding feasible solution; Modified distribution method for finding minimum cost supply-demand solution
  3. Minimum cost flow problem; Network simplex method
  4. Prim’s and Kruskal’s algorithm for minimum spanning trees
  5. Shortest math problem; Dijkstra algorithm
  6. Travelling sales man problem; application of branch and bound
  7. Application of Genetic algorithm, Tabu search and hill climbing in network design and optimisation (including cost optimisation) - (subject to time availability)
  8. Modelling network redundancies; cost consideration of adding redundancies (as a multiobjective optimisation example)
  9. Obtaining availability and reliability figures; application of mean time to failure and mean time to repair and the relevant formulations
  10. Little’s formula, Deterministic queuing models; Birth-Death process Queue models such as M/M/k, M/M/k/k, finite buffer, finite source, state dependent models; queuing networks, and telecommunication applications; Recursion of Erlang B formula

Generic skills

On completion of this subject, the students should have developed the following skills:

  • Problem solving and analytical skills;
  • Critical and creative thinking, with an aptitude for continued self-directed learning;
  • Sense of intellectual curiosity;
  • Ability to interpret data and research results;
  • Ability to learn in a range of ways, including through information and communication technologies;
  • Capacity to confront unfamiliar problems;
  • Ability to evaluate and synthesise the research and professional literature;
  • Ability to develop models of practical applications and evaluate their performance by rigorous analytical means.

Last updated: 19 June 2019