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Unit outline_

COMP9121: Design of Networks and Distributed Systems

Semester 2, 2020 [Normal evening] - Camperdown/Darlington, Sydney

The unit covers general foundations of communication systems and a detailed walk through of the implementation of the TCP/IP protocol stack, which forms the basis of the Internet. The unit also covers the basic knowledge of how to analyse, design and implement simple communication protocols. On completion of this unit students will have developed an understanding of the principles and practice of the layered model of communications architecture, the TCP/IP protocol stack and its component protocols, and various common techniques and tools for protocol analysis and design.

Unit details and rules

Academic unit Computer Science
Credit points 6
Prerequisites
? 
None
Corequisites
? 
None
Prohibitions
? 
COMP5116
Assumed knowledge
? 

None

Available to study abroad and exchange students

No

Teaching staff

Coordinator Wei Bao, wei.bao@sydney.edu.au
Type Description Weight Due Length
Final exam (Open book) Type C final exam Final exam
Type C
60% Formal exam period 2 hours
Outcomes assessed: LO1 LO2 LO3 LO4 LO5
Assignment Assignment 1
20% Week 07 n/a
Outcomes assessed: LO1 LO2 LO3 LO4
Assignment Assignment 2
20% Week 12 n/a
Outcomes assessed: LO1 LO2 LO3 LO4 LO5
Type C final exam = Type C final exam ?

Assessment summary

Assignment 1 20%. Covers Weeks 1-6

Assignment 2 20%. Covers Weeks 7-12

Final exam 60%. Covers Weeks 1-12

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.

It is a policy of the School of Computer Science that in order to pass this unit, a student must achieve at least 40% in the written examination. For subjects without a final exam, the 40% minimum requirement applies to the corresponding major assessment component specified by the lecturer. A student must also achieve an overall final mark of 50 or more. Any student not meeting these requirements may be given a maximum final mark of no more than 45 regardless of their average.

 

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:

Consistent penalty of 5% per day late. Assignments more than 10 days late get 0.

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.

Use of generative artificial intelligence (AI) and automated writing tools

You may only use generative AI and automated writing tools in assessment tasks if you are permitted to by your unit coordinator. If you do use these tools, you must acknowledge this in your work, either in a footnote or an acknowledgement section. The assessment instructions or unit outline will give guidance of the types of tools that are permitted and how the tools should be used.

Your final submitted work must be your own, original work. You must acknowledge any use of generative AI tools that have been used in the assessment, and any material that forms part of your submission must be appropriately referenced. For guidance on how to acknowledge the use of AI, please refer to the AI in Education Canvas site.

The unapproved use of these tools or unacknowledged use will be considered a breach of the Academic Integrity Policy and penalties may apply.

Studiosity is permitted unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission as detailed on the Learning Hub’s Canvas page.

Outside assessment tasks, generative AI tools may be used to support your learning. The AI in Education Canvas site contains a number of productive ways that students are using AI to improve their learning.

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 and overview Lecture (2 hr) LO1 LO2 LO3
Delay and bit error Tutorial (1 hr) LO1 LO4
Week 02 Data link layer 1 Lecture (2 hr) LO1 LO2 LO3 LO4
Data link layer Tutorial (1 hr) LO1 LO4
Week 03 Data link layer 2 Lecture (2 hr) LO1 LO2 LO3 LO4
Data link layer simulator by Python Tutorial (1 hr) LO1
Week 04 Network layer 1 Lecture (2 hr) LO1 LO2 LO3
Network layer Tutorial (1 hr) LO1 LO2 LO3
Week 05 Network layer 2 Lecture (2 hr) LO1 LO2 LO3 LO4
Routing protocols Tutorial (1 hr) LO1 LO2 LO3 LO4
Week 06 Network layer 3 Lecture (2 hr) LO1 LO2 LO3
Wireshark Tutorial (1 hr) LO3
Week 07 1. Software-defined networking; 2. Transport layer 1 Lecture (2 hr) LO1 LO2 LO3
NAT Tutorial (1 hr) LO2 LO3
Week 08 Transport layer 2: TCP and UDP Lecture (2 hr) LO1 LO2 LO3
TCP and Telnet Tutorial (1 hr) LO2 LO3
Week 09 Application layer 1 Lecture (2 hr) LO1 LO2 LO3
TCP and cross-layer analysis Tutorial (1 hr) LO1 LO2 LO3
Week 10 1. Application layer 2; 2. Network security 1 Lecture (2 hr) LO1 LO2 LO3 LO5
DNS and HTTP Tutorial (1 hr) LO1 LO2 LO3
Week 11 Network security 2 Lecture (2 hr) LO1 LO2 LO3 LO5
Hash and public/private keys Tutorial (1 hr) LO5
Week 12 1. Network security 3; 2. Review Lecture (2 hr) LO1 LO2 LO3 LO4 LO5
TLS and firewall Tutorial (1 hr) LO5

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.

  • James F. Kurose, Keith W. Ross, Computer Networking, a top-Down Approach (6th Edition). Pearson International Edition, 978-0-273-76896- 8.
  • Andrew Tanenbaum, Computer Networks, Fifth Edition (5th). USA, Prentice Hall, 2010. 0-13-212695-8.

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. understand and be able to use common techniques and tools for protocol analysis
  • LO2. understand the fundamentals of the TCP/IP protocol stack, and its component protocols
  • LO3. understand the principles and practice of the layered model of communications architecture
  • LO4. understand the network performance analysis by basic math tools
  • LO5. understand network security and its applications

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 significant 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.