Skip to main content
Unit outline_

COMP9601: Computer and Network Organisation

Semester 1, 2023 [Normal evening] - Remote

This unit of study provides an introduction to computer organisation and network protocols. It covers a broad range of topics including computer hardware, software architecture (operating systems, compilers, etc), and principles of communication network protocols. It is designed to give students an understanding of how software programs operate and run inside the computer hardware, and therefore the knowledge how to use computers most effectively.

Unit details and rules

Academic unit Computer Science
Credit points 6
Prerequisites
? 
None
Corequisites
? 
None
Prohibitions
? 
COMP5213
Assumed knowledge
? 

None

Available to study abroad and exchange students

Yes

Teaching staff

Coordinator Albert Zomaya, albert.zomaya@sydney.edu.au
Lecturer(s) Omid Tavallaie, omid.tavallaie@sydney.edu.au
Type Description Weight Due Length
Supervised exam
? 
Final exam
This is a closed book examination - specified materials permitted.
60% Formal exam period 2 hours
Outcomes assessed: LO1 LO2 LO3 LO4
Assignment Assignment 3
Groupwork assessment comprises 15% of the total mark
20% STUVAC
Due date: 02 Jun 2023 at 23:59

Closing date: 12 Jun 2023
n/a
Outcomes assessed: LO2 LO3
Assignment Assignment 1
Individual assessment comprises 5% of the total mark
10% Week 07
Due date: 04 Apr 2023 at 23:59

Closing date: 14 Apr 2023
n/a
Outcomes assessed: LO4
Assignment Assignment 2
Individual assessment comprises 10% of the total mark
10% Week 11
Due date: 09 May 2023 at 23:59

Closing date: 19 May 2023
n/a
Outcomes assessed: LO3 LO1

Assessment summary

Assignment 1: 10%;

Assigment 2: 10%;

Aassignment 3: 20%

At least 40% of the final exam mark must be received.

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 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 Lecture (2 hr) LO1
Week 02 Data Representation in Computer Systems (Part 1) Lecture (2 hr) LO4
Base conversion Computer laboratory (1 hr) LO4
Week 03 Data Representation in Computer Systems (Part 2) Lecture (2 hr) LO4
ASCII characters and floating-point representation Computer laboratory (1 hr) LO4
Week 04 Boolean Algebra and Logic Gates Lecture (2 hr) LO4
Truth tables and Boolean functions Computer laboratory (1 hr) LO4
Week 05 Processor Architecture (Part 1) Lecture (2 hr) LO1
Memory addressing and basic Unix/Linux commands Computer laboratory (1 hr) LO1
Week 06 Processor Architecture (Part 2) Lecture (2 hr) LO1
Javap command Computer laboratory (1 hr) LO1
Week 07 Instruction Set Architectures Lecture (2 hr) LO1 LO3
Java virtual machine Computer laboratory (1 hr) LO1 LO3
Week 08 Memory Hierarchy Lecture (2 hr) LO3
Cache memory Computer laboratory (1 hr) LO3
Week 09 Input/Output and Storage Systems Lecture (2 hr) LO3
Amdahl's law and magnetic disk technology Computer laboratory (1 hr) LO3
Week 10 Internet and Protocols Lecture (2 hr) LO2
Message format in network layers Computer laboratory (1 hr) LO2
Week 11 Internetworking Lecture (2 hr) LO2
Network delays Computer laboratory (1 hr) LO2
Week 12 Web Cache and Performance Measurements Lecture (2 hr) LO2 LO3
Performance measurement Computer laboratory (1 hr) LO2 LO3

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.

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 the architecture of computer, especially instruction set, memory hierarchy and processor architecture through the introduction of a simplified processor that can run Java bytecode
  • LO2. understand network architecture and protocols (especially application level protocols and TCP/IP) and making effective use of a network tool and programming interface
  • LO3. study technical concepts and details, and present research reports (e.g., cache replacement policies and their advantages and disadvantages)
  • LO4. understand different number representations (i.e., binary, hexadecimal and decimal) and make use of these in the assembly language level.

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.