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.