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We are aiming for an incremental return to campus in accordance with guidelines provided by NSW Health and the Australian Government. Until this time, learning activities and assessments will be planned and scheduled for online delivery where possible, and unit-specific details about face-to-face teaching will be provided on Canvas as the opportunities for face-to-face learning become clear.

We are currently working to resolve an issue where some unit outline links are unavailable. If the link to your unit outline does not appear below, please use the link in your Canvas site. If no link is available on your Canvas site, please contact your unit coordinator.

Unit of study_

COMP5313: Large Scale Networks

The growing connected-ness of modern society translates into simplifying global communication and accelerating spread of news, information and epidemics. The focus of this unit is on the key concepts to address the challenges induced by the recent scale shift of complex networks. In particular, the course will present how scalable solutions exploiting graph theory, sociology and probability tackle the problems of communicating (routing, diffusing, aggregating) in dynamic and social networks.

Code COMP5313
Academic unit Computer Science
Credit points 6
Prerequisites:
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None
Corequisites:
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None
Prohibitions:
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None
Assumed knowledge:
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Basic knowledge of computer networks as covered in INFO1112 or COMP9201 or COMP9601 (or equivalent UoS from different institutions).

At the completion of this unit, you should be able to:

  • LO1. interpret the fundamental structures, dynamics and resource distribution in such models
  • LO2. explain key factors that impact the accuracy and speed of information dissemination and aggregation
  • LO3. evaluate the asymptotic complexity and accuracy of graph algorithms
  • LO4. describe various types of network models in different contexts like computer science, society or markets
  • LO5. identify and assess accurately the role of networks in number of physical settings
  • LO6. identify and describe the technical issues that affect the dissemination of information in a network
  • LO7. analyse probabilistically the relations between communicating entities of a network
  • LO8. analyse the stochastic methods necessary to evaluate the convergence of various algorithms
  • LO9. recognise probabilistic solutions to problems that have no deterministic solutions and apply them thoroughly
  • LO10. compare experimentally and theoretically the adequacy of different probabilistic solutions.

Unit outlines

Unit outlines will be available 2 weeks before the first day of teaching for 1000-level and 5000-level units, or one week before the first day of teaching for all other units.

There are no unit outlines available online for previous years.