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Distributed Algorithms (COMP90020)
Graduate courseworkPoints: 12.5On Campus (Parkville)
About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable(opens in new window)
Contact information
Semester 1
Overview
Availability | Semester 1 |
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Fees | Look up fees |
AIMS
The Internet, World Wide Web, bank networks, mobile phone networks and many others are examples for Distributed Systems. Distributed Systems rely on a key set of algorithms and data structures to run efficiently and effectively. In this subject, we learn these key algorithms that professionals work with while dealing with various systems. Clock synchronization, leader election, mutual exclusion, and replication are just a few areas were multiple well known algorithms were developed during the evolution of the Distributed Computing paradigm.
INDICATIVE CONTENT
Topics covered include:
- Synchronous and asynchronous network algorithms that address resource allocation, communication
- Consensus among distributed processes
- Distributed data structures
- Data consistency
- Deadlock detection
- Lader election, and
- Global snapshots issues.
Intended learning outcomes
INTENDED LEARNING OUTCOMES (ILO)
On completion of this subject the student is expected to:
- Have developed an understanding of distributed algorithm design
- Be able to implement and analyse distributed algorithms.
Generic skills
On completion of this subject students should have the following skills:
- Ability to undertake problem identification, formulation and solution
- Capacity for independent critical thought, rational inquiry and self-directed learning
- Profound respect for truth and intellectual integrity, and for the ethics of scholarship.
Last updated: 3 November 2022
Eligibility and requirements
Prerequisites
Code | Name | Teaching period | Credit Points |
---|---|---|---|
COMP90015 | Distributed Systems |
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
Corequisites
None
Non-allowed subjects
None
Inherent requirements (core participation requirements)
The University of Melbourne is committed to providing students with reasonable adjustments to assessment and participation under the Disability Standards for Education (2005), and the Assessment and Results Policy (MPF1326). Students are expected to meet the core participation requirements for their course. These can be viewed under Entry and Participation Requirements for the course outlines in the Handbook.
Further details on how to seek academic adjustments can be found on the Student Equity and Disability Support website: http://services.unimelb.edu.au/student-equity/home
Last updated: 3 November 2022
Assessment
Additional details
- Term project including a report (2000 words) and a 10 minute presentation (together worth 40% of the final mark), requiring approximately 50 - 55 hours of work, due week 10-12 of the semester
- One 3-hour written examination (60% of the final mark).
Intended Learning Outcome (ILO) 1 is assessed by all the components. ILO 2 is assessed by the project component. All components should be completed satisfactorily to obtain a passing mark in this subject.
Last updated: 3 November 2022
Dates & times
- Semester 1
Principal coordinator Lars Kulik Mode of delivery On Campus (Parkville) Contact hours 3 hours contact per week Total time commitment 200 hours Teaching period 27 February 2017 to 28 May 2017 Last self-enrol date 10 March 2017 Census date 31 March 2017 Last date to withdraw without fail 5 May 2017 Assessment period ends 23 June 2017 Semester 1 contact information
Time commitment details
200 hours
Last updated: 3 November 2022
Further information
- Texts
Prescribed texts
None
- Subject notes
LEARNING AND TEACHING METHODS
The subject will be delivered through a combination of lectures, tutorials, student presentations. Students will write a report and give a presentation.
INDICATIVE KEY LEARNING RESOURCES
The subject accesses a number of scholarly papers in the area which are presented through lecture slides. Papers are made available through LMS to the students. The subject also uses: Distributed Systems: Concepts and Design by Coulouris, Dollimore, Kindberg, and Blair, Fifth Edition, Addison-Wesley.
CAREERS / INDUSTRY LINKS
Distributed Algorithms are fundamental to understanding any Distributed System and multiple key information and communication technologies, these include but are not limited to the Internet, Banking Networks, and Mobile Systems.
- Related Handbook entries
This subject contributes to the following:
Type Name Course Master of Data Science Course Master of Science (Computer Science) Course Doctor of Philosophy - Engineering Course Master of Philosophy - Engineering Course Master of Information Technology Course Master of Information Technology Course Ph.D.- Engineering Informal specialisation Computer Science Informal specialisation Master of Engineering (Mechatronics) Informal specialisation Master of Engineering (Software) Specialisation (formal) Software Specialisation (formal) Mechatronics Major MIT Distributed Computing Specialisation Major Computer Science Specialisation (formal) Distributed Computing - Available through the Community Access Program
About the Community Access Program (CAP)
This subject is available through the Community Access Program (also called Single Subject Studies) which allows you to enrol in single subjects offered by the University of Melbourne, without the commitment required to complete a whole degree.
Entry requirements including prerequisites may apply. Please refer to the CAP applications page for further information.
Additional information for this subject
Subject coordinator approval required
Last updated: 3 November 2022