Outline

Overview

The unit will cover the following specific material: 1) communication reference models (TCP/IP and OSI), 2) circuit-switched and packet-switched communication, 3) network node functions and building blocks, 4) LAN, MAN, WAN, and WLAN technologies, 5) data transfer and routing algorithms and protocols between networks, 6) wireless networks (4G, WiFi, 5G and Bluetooth), 7) TCP/IP core protocols (IP, ICMP, ARP, TCP, UDP etc. ), 8) applications and protocols (FTP, Telnet, SMTP, HTTP, DHCP, DNS etc. ), and 9) network management and security.

Unit details and rules

Academic unit	School of Electrical and Computer Engineering
Credit points	6
Prerequisites ?	None
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	Students should be familiar with fundamental digital technologies and representations (e.g., bit complement and internal word representation), have a basic understanding of the physical properties of communication channels, techniques and limitations, and be able to apply fundamental mathematical skills.
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Wibowo Hardjawana, wibowo.hardjawana@sydney.edu.au

Assessment

The census date for this unit availability is 1 September 2025

Details
Criteria

Type	Description	Weight	Due	Length	Use of AI
Written exam ?	Final Exam Essay-type: Analytical questions on topics with answers requiring calculation and/or short explanations	48%	Formal exam period	2 hours	AI prohibited
Outcomes assessed:
Practical skill	Lab reports 4 labs 8 mark each	32%	Multiple weeks	—	AI allowed
Outcomes assessed:
Out-of-class quiz	Quiz 1 Quiz 1 in Canvas	10%	Week 06 Due date: 14 Sep 2025 at 23:59 Closing date: 14 Sep 2025	30 minutes	AI allowed
Outcomes assessed:
Out-of-class quiz	Quiz 2 Quiz 2 in Canvas	10%	Week 10 Due date: 19 Oct 2025 at 23:59 Closing date: 19 Oct 2025	30 minutes	AI allowed
Outcomes assessed:
= group assignment ?

Assessment summary

Final Exam: 38%
Quizzes: Quizes will be on weeks 6 and 10 = 20%
Assignments: 4 Lab reports = 32%

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.

Use of generative artificial intelligence (AI)

You can use generative AI tools for open assessments. Restrictions on AI use apply to secure, supervised assessments used to confirm if students have met specific learning outcomes.

Refer to the assessment table above to see if AI is allowed, for assessments in this unit and check Canvas for full instructions on assessment tasks and AI use.

If you use AI, you must always acknowledge it. Misusing AI may lead to a breach of the Academic Integrity Policy.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

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:

No late submissions are allowed from Quizzes. Any assignment work submitted after 11:59pm on the due date will be penalised by 5% of the maximum awardable mark for each calendar day after the due date. If the assessment is submitted more than ten calendar days late, a mark of zero will be awarded.

Academic integrity

The University expects students to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

Our website provides information on academic integrity and the resources available to all students. This includes advice on how to avoid common breaches of academic integrity. Ensure that you have completed the Academic Honesty Education Module (AHEM) which is mandatory for all commencing coursework students

Penalties for serious breaches can significantly impact your studies and your career after graduation. It is important that you speak with your unit coordinator if you need help with completing assessments.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

Learning support

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.

Support for students

The Support for Students Policy reflects the University’s commitment to supporting students in their academic journey and making the University safe for students. It is important that you read and understand this policy so that you are familiar with the range of support services available to you and understand how to engage with them.

The University uses email as its primary source of communication with students who need support under the Support for Students Policy. Make sure you check your University email regularly and respond to any communications received from the University.

Learning resources and detailed information about weekly assessment and learning activities can be accessed via Canvas. It is essential that you visit your unit of study Canvas site to ensure you are up to date with all of your tasks.

If you are having difficulties completing your studies, or are feeling unsure about your progress, we are here to help. You can access the support services offered by the University at any time:

Support and Services (including health and wellbeing services, financial support and learning support)
Course planning and administration
Meet with an Academic Adviser

Weekly schedule

WK	Topic	Learning activity
Multiple weeks	Student's independent learning hours at their own time	Independent study (68 hr)
Week 01	Background and preview: an introduction to the Internet	Lecture (4 hr)
Week 02	Physical layer	Lecture and tutorial (4 hr)
Week 03	Data link layer	Lecture and tutorial (4 hr)
Week 04	Local Area Networks	Lecture and tutorial (4 hr)
Week 05	Network Layer – Data Transfer, Routing Protocols and Algorithms	Lecture and tutorial (4 hr)
Week 06	Network Layer – Data Transfer, Routing Protocols and Algorithms	Lecture and tutorial (4 hr)
Week 07	Network Layer – Data Transfer, Routing Protocols and Algorithms	Lecture and tutorial (4 hr)
Week 08	Transport Layer	Lecture and tutorial (4 hr)
Week 09	Application layer	Lecture and tutorial (4 hr)
Week 10	WAN Technologies	Lecture (4 hr)
Week 11	QoS in IP networks	Lecture and tutorial (4 hr)
Week 12	Wireless Networks and Network Security	Lecture and tutorial (4 hr)
Week 13	Guest Lectures	Lecture and tutorial (4 hr)

Attendance and class requirements

Laboratory: The labs are designed to greatly deepen students` understanding of network protocols by seeing them in action. The labs cover various layers of internet protocols, and will give students the opportunity to observe the sequence of messages exchanged between two protocol entities, and to even try different parameters in some protocols to watch the effects.
Tutorial: Tutorials are designed to help student understand the materials from the lectures, as well as the textbook.
Independent Study: The introductory nature of this UoS means that students will encounter various pieces of knowledge in networking areas. Therefore, independent study is essential for a successful completion.

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.

Behrouz A. Forouzan, Data Communications and Networking with TCP/IP Protocol Suite, 6th ed., 2022
J. F. Kurose and K. W. Ross, Computer Networking: A Top-Down Approach, 8th ed., 2022
J. F. Kurose and K. W. Ross, Computer Networking: A Top-Down Approach, 6th ed., 2013

Learning outcomes

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.

Outcomes
Graduate qualities

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

LO1. write reports to communicate complex and technical material clearly and concisely, addressing a specific target audience
LO2. work in a team by drawing on the abilities and knowledge of others, emphasising and fulfilling clear responsibilities, and leading in the development of a consensus to the specific engineering problem at hand
LO3. solve ill-defined network problems by employing techniques and principles of protocol design, implementation, and analysis
LO4. demonstrate an understanding of concepts in data communications and networking, and the advantages and disadvantages of alternative protocols, algorithms, and designs
LO5. demonstrate proficiency in assessing and troubleshooting different networks using specific network tools, such as packet sniffer to the extent presented in the course
LO6. apply principles and concepts of communication and networking protocols, algorithms, and designs to specific engineering problems and situations to the extent of the material presented
LO7. demonstrate an understanding of network protocols and algorithms using fundamental mathematical derivations.

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
Learning outcomes

Responding to student feedback

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

No major 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.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links

ELEC3506: Communications Networks

Semester 2, 2025 [Normal day] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links