Network Technology

Module summary

Module code: COMP1664
Level: 6
Credits: 15
School: Liberal Arts and Sciences
Department: Computing and Mathematical Sci.
Module Coordinator(s): Dimitrios Frangiskatos


Pre and co requisites

Strong numeracy, strong understanding of number systems (decimal, hexadecimal and binary, and conversion between these), strong (level 5) knowledge of network technology and networking concepts.


This course provides students with an in-depth understanding of network technology necessary to make informed selections for particular scenarios, and an in-depth understanding of network performance and the factors that influence it.
The course builds upon students’ level 4 and level 5 knowledge of networking concepts.
The aims are:
To instil a thorough and practical understanding of network technologies, their operational characteristics, strengths and weaknesses.
To be able to critically evaluate technologies and to compare and contrast amongst alternatives.
To enable the student to choose the appropriate technologies and configuration to meet an organisation's needs.

Learning outcomes

On successful completion of this course a student will be able to:
1 Compare and critique network types, protocol architectures, hardware and software components, and evaluate their pros and cons.
2 Connect and integrate various network technologies to achieve required configurations and end-to-end systems.
3 Evaluate behavioural aspects of networks and the ways in which network traffic and network performance interplay.
4 Design, build and use models of networks and evaluate their performance.

Indicative content

Brief refresh of material already covered in levels 4 and 5 {communication basics, network types, data transmission, switching, multiplexing, routing, addressing, error recovery, congestion control}.
Layered architectures and encapsulation (OSI, TCP/IP, IEEE 802.x), standards and bodies.
LANs, Ethernet, FDDI, IPv4, IPv6, TCP, UDP. Wide Area Networks.
Wireless networks, Wireless PANs (ZigBee).
Application-specific network technologies (e.g. CAN).
Network models and their use to evaluate network performance.

Teaching and learning activity

Concepts will be introduced in lectures. Practical work will be through supervised laboratory sessions. Unsupervised, guided self-study will extend the amount of time students spend doing practical laboratory activities.

Learning Time (1 credit = 10 hours).
Scheduled contact hours: Lectures 24, Supervised practical sessions 12.
Guided independent study: Coursework 50, Independent laboratory work 40.
Other non-scheduled time 24 (e.g. reading).
Total hours 150.


Method of Summative assessment: Individual Coursework
Outcomes assessed:1,2,3,4
Grading Mode (e.g. pass/ fail; %): %
Weighting % : 100%
Passmark: 40%
Outline Details: Develop and use a network model to examine the performance (and factors that affect the performance of) a given network. Full details of the coursework task and the associated marking scheme are provided in the detailed coursework specification document.

Nature of FORMATIVE assessment supporting student learning:
Students will implement the network model specified in the summative assessment. As part of this, during scheduled laboratory classes each student will be required to provide regular demonstrations of progress, for which they will be given instant verbal feedback relating to the quality of their work. There will also be a final demonstration of the developed network model, where detailed verbal feedback will be given, the assessment of which feeds into the final coursework mark. Detailed and categorised written feedback will be provided for both the interim coursework report (which is an optional upload specifically for the purpose of providing feedback at an early stage in the coursework development lifecycle) and the final coursework report.