Handbook

COMP90020 Distributed Algorithms

Credit Points: 12.50
Level: 9 (Graduate/Postgraduate)
Dates & Locations:

This subject has the following teaching availabilities in 2012:

Semester 2, Parkville - Taught on campus.Show/hide details
Pre-teaching Period Start not applicable
Teaching Period not applicable
Assessment Period End not applicable
Last date to Self-Enrol not applicable
Census Date not applicable
Last date to Withdraw without fail not applicable


Timetable can be viewed here.
For information about these dates, click here.
Time Commitment: Contact Hours: 24 hours of lectures, 12 hours of tutorial/laboratory classes; Non-contact time commitment: 84 hours
Total Time Commitment:

120 hours

Prerequisites:
Subject
Study Period Commencement:
Credit Points:
Semester 1, Semester 2
12.50
Corequisites:

None

Recommended Background Knowledge:

None

Non Allowed Subjects:

None

Core Participation Requirements:

For the purposes of considering request for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Students Experiencing Academic Disadvantage Policy, academic requirements for this subject are articulated in the Subject Description, Subject Objectives, Generic Skills and Assessment Requirements of this entry. The University is dedicated to provide support to those with special requirements. Further details on the disability support scheme can be found at the Disability Liaison Unit website: http://www.services.unimelb.edu.au/disability/

Coordinator

Assoc Prof Egemen Tanin

Contact

Dr Adrian Pearce

email: adrianrp@unimelb.edu.au

Subject Overview:

Topics covered include: synchronous and asynchronous network algorithms that address resource allocation, communication, consensus among distributed processes, distributed data structures, data consistency, deadlock detection, leader election, and global snapshots issues in distributed systems.

Objectives:

On successful completion students should:

  • Have developed an understanding of distributed algorithm design
  • Be able to implement and analyse distributed algorithms
  • Be able to undertake problem identification, formulation and solution

Assessment:

Assignments on devising, analysing, and applying algorithms to solve real world problems during semester (40%) and a 3-hour written examination (60%). All components must be completed satisfactorily to pass the subject.

Prescribed Texts:

None

Breadth Options:

This subject is not available as a breadth subject.

Fees Information: Subject EFTSL, Level, Discipline & Census Date
Generic Skills:

On completion of this subject students should:

  • Have a capacity for independent critical thought, rational inquiry and self-directed learning; and
  • Have a profound respect for truth and intellectual integrity, and for the ethics of scholarship
Related Course(s): Bachelor of Computer Science (Honours)
Master of Engineering in Distributed Computing
Master of Science (Computer Science)
Master of Software Systems Engineering
Related Majors/Minors/Specialisations: Computer Science
Master of Engineering (Software)

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