Useful links
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.
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:
?
|
None |
|---|---|
|
Corequisites:
?
|
None |
| Prohibitions:
?
|
None |
| Assumed knowledge:
?
|
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.
- Key dates
Key dates through the academic year, including teaching periods, census, payment deadlines and exams.
- Student administration
Enrolment, course planning, fees, graduation, support services, student IT
- Expectations of student conduct
Code of Conduct for Students, Conditions of Enrollment, University Privacy Statement, Academic Integrity
- Academic appeals
Academic appeals process, special consideration, rules and guidelines, advice and support
- Learning and teaching policy
Policy register, policy search
- Financial support
Scholarships, interest free loans, bursaries, money management
- Study resources
Learning Centre, faculty and school programs, Library, online resources
- Health and support
Student Centre, counselling & psychological services, University Health Service, general health and wellbeing
