Note: This is an archived Handbook entry from 2015.
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This subject has the following teaching availabilities in 2015:Semester 1, Parkville - Taught on campus.
Timetable can be viewed here. For information about these dates, click here.
|Time Commitment:||Contact Hours: 3 hours per week |
Total Time Commitment:
Study Period Commencement:
Semester 1, Semester 2
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CoordinatorProf Richard Sinnott
The growing popularity of the Internet along with the availability of powerful computers and high-speed networks as low-cost commodity components are changing the way we do parallel and distributed computing (PDC). Cluster and Cloud Computing are two approaches for PDC. Clusters employ cost-effective commodity components for building powerful computers within local-area networks. Recently, “cloud computing” has emerged as the new paradigm for delivery of computing as services in a pay-as-you-go-model via the Internet. These approaches are used to tackle may research problems with particular focus on "big data" challenges that arise across a variety of domains.
Some examples of scientific and industrial applications that use these computing platforms are: system simulations, weather forecasting, climate prediction, automobile modelling and design, high-energy physics, movie rendering, business intelligence, big data computing, and delivering various business and consumer applications on a pay-as-you-go basis.
This subject will enable students to understand these technologies, their goals, characteristics, and limitations, and develop both middleware supporting them and scalable applications supported by these platforms.
This subject is an elective subject in the Master of Information Technology and a mandatory for the Distributed Computing Specialisation. It can also be taken as an Advanced Elective subject in the Master of Engineering (Software).
INTENDED LEARNING OUTCOMES (ILO)
On completion of this subject the student is expected to:
Hurdle requirement: To pass the subject students must obtain at least:
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This subject is not available as a breadth subject.
|Fees Information:||Subject EFTSL, Level, Discipline & Census Date|
On completion of this subjects students should have the following skills:
LEARNING AND TEACHING METHODS
The subject will be delivered through a combination of lectures and both individual and team-based learning. In team-based learning, a group of students will jointly develop applications.
INDICATIVE KEY LEARNING RESOURCES
Students will have access to lecture notes and lecture slides. The subject LMS site also contains links to recommended literature and current survey papers of cluster and cloud computing principles.
CAREERS / INDUSTRY LINKS
Adoption of the technologies taught in this subject, and in particular cloud computing, is growing quickly. All the big players in the ICT market offer at least one product that is based on these technologies. Therefore, there are many opportunities for professionals that understand them and are able to develop applications and support software for them. Some examples of commercial companies playing a major role in Cloud computing area are: Amazon, IBM, Microsoft, Google, Oracle, CA, VMWare, and Citrix. The area of "Big data" is also one of the "hot topics" in great demand in the industry at present.
Master of Information Technology |
Master of Information Technology
Master of Philosophy - Engineering
Master of Science (Computer Science)
Master of Software Systems Engineering
Computer Science |
MIT Distributed Computing Specialisation
Master of Engineering (Software)
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