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Unit of study_

COMP3221: Distributed Systems

Semester 1, 2023 [Normal day] - Camperdown/Darlington, Sydney

This unit will provide a broad introduction to the principles of distributed computing and distributed systems and their design; provide students the fundamental knowledge required to analyse, design distributed algorithms and implement various types of applications, like distance-vector routing protocol; explain the common algorithmic design principles and approaches used in the design of message passing at different scales (e.g., logical time, peer-to-peer overlay).

Unit details and rules

Unit code COMP3221
Academic unit Computer Science
Credit points 6
Prohibitions
? 
COMP2121
Prerequisites
? 
(INFO1105 OR INFO1905) OR ((INFO1103 OR INFO1113) AND (COMP2123 OR COMP2823))
Corequisites
? 
None
Assumed knowledge
? 

None

Available to study abroad and exchange students

Yes

Teaching staff

Coordinator Nguyen Tran, nguyen.tran@sydney.edu.au
Type Description Weight Due Length
Supervised exam
? 
hurdle task
Final Exam
CC students: Pen and paper on campus. OL/RE students: Canvas with ProctorU.
50% Formal exam period 2 hours
Outcomes assessed: LO2 LO3 LO4 LO5 LO6 LO7
Assignment Assignment 1
Programming assignment.
15% Week 05
Due date: 24 Mar 2023 at 23:59
2-3 weeks
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6
Assignment Assignment 2
Programming assignment.
15% Week 08
Due date: 21 Apr 2023 at 23:59
2-3 weeks
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6
Assignment Assignment 3
Programming assignment.
20% Week 11
Due date: 12 May 2023 at 23:59
3-4 weeks
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6 LO7
hurdle task = hurdle task ?

Assessment summary

  • Assignment 1 – writing a computer program to solve a given task.
  • Assignment 2 – writing a computer program to solve a given task and a report discussing the results.
  • Assignment 3 – writing a computer program to solve a given task and a report discussing the results.
  • Exam – online exam at the end of the semester (less than 40% is automatically a FAIL)

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name

Mark range

Description

High distinction

85 - 100

 

Distinction

75 - 84

 

Credit

65 - 74

 

Pass

50 - 64

 

Fail

0 - 49

When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see sydney.edu.au/students/guide-to-grades.

For more information see guide to grades.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

  • Deduction of 5% of the maximum mark for each calendar day after the due date.
  • After ten calendar days late, a mark of zero will be awarded.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

For all assignments: a penalty of 5% per day late will apply. Late submissions will not be accepted after 5 days late, because we will be returning the marked assignments quickly.

Academic integrity

The Current Student website  provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.  

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

You may only use artificial intelligence and writing assistance tools in assessment tasks if you are permitted to by your unit coordinator, and if you do use them, you must also acknowledge this in your work, either in a footnote or an acknowledgement section.

Studiosity is permitted for postgraduate units unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission.

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

WK Topic Learning activity Learning outcomes
Week 01 Introduction Lecture (2 hr) LO4
Week 02 Architecture Lecture and tutorial (2 hr) LO4
Tutorial: Multi-Threading Lecture and tutorial (1 hr) LO6
Week 03 Communication (Routing) Lecture and tutorial (2 hr) LO4
Tutorial: Routing Lecture and tutorial (1 hr) LO6
Week 04 Communication (TCP) and Naming Lecture and tutorial (2 hr) LO5
Tutorial: Client-Server Communication Lecture and tutorial (1 hr) LO6
Week 05 Distributed Optimization Lecture and tutorial (2 hr) LO4 LO7
Tutorial: Distributed Optimization Lecture and tutorial (1 hr) LO7
Week 06 Distributed Machine Learning Lecture and tutorial (2 hr) LO4 LO7
Tutorial: Distributed Machine Learning Lecture and tutorial (1 hr) LO7
Week 07 Blockchain Lecture and tutorial (2 hr) LO4
Tutorial: Blockchain Lecture and tutorial (1 hr) LO4
Week 08 Concensus Lecture and tutorial (2 hr) LO4
Tutorial: Concensus Lecture and tutorial (1 hr) LO4
Week 09 Robustness Lecture and tutorial (2 hr) LO4 LO6
Tutorial: Robustness Lecture and tutorial (1 hr) LO2 LO3 LO4 LO6
Week 10 Security Lecture and tutorial (2 hr) LO2 LO3 LO4
Tutorial: Security Lecture and tutorial (1 hr) LO3 LO4
Week 11 Scalability Lecture and tutorial (2 hr) LO4 LO6
Tutorial: Scalability Lecture and tutorial (1 hr) LO6
Week 12 Other challenges Lecture and tutorial (2 hr) LO2 LO4
Tutorial: Other challenges Lecture and tutorial (1 hr) LO2
Week 13 Review Lecture and tutorial (2 hr) LO4

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Required readings

All readings for this unit can be accessed through the Library eReserve, available on Canvas.

Van Steen and Tanenbaum, Distributed Systems Principles and Paradigms, 2nd edition.

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

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

  • LO1. produce professional quality written assignments and reports as well as well-documented software for reuse
  • LO2. evaluate the implications of sharing of information and the importance of privacy and security as well as appreciate the importance of ethical behaviour among users of distributed systems
  • LO3. design efficient distributed algorithms and produce distributed software based on these designs
  • LO4. understand the general properties of distributed systems. You should be familiar with various types of distributed applications and how information is shared between distributed components
  • LO5. understand programming paradigms for distributed systems (e.g. sockets) and be able to apply them to protocols
  • LO6. implement distributed algorithms. You will be able to able to apply some common distributed algorithms (e.g. searches, shortest path, trees) towards solving problems.
  • LO7. understand and implement distributed and scalable machine learning algorithms for large-scale networks.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1 Depth of disciplinary expertise

Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.

GQ2 Critical thinking and problem solving

Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.

GQ3 Oral and written communication

Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.

GQ4 Information and digital literacy

Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.

GQ5 Inventiveness

Generating novel ideas and solutions.

GQ6 Cultural competence

Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.

GQ7 Interdisciplinary effectiveness

Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.

GQ8 Integrated professional, ethical, and personal identity

An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.

GQ9 Influence

Engaging others in a process, idea or vision.

Outcome map

Learning outcomes Graduate qualities
GQ1 GQ2 GQ3 GQ4 GQ5 GQ6 GQ7 GQ8 GQ9

This section outlines changes made to this unit following staff and student reviews.

No changes have been made since this unit was last offered

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.