Course Title: Wireless Sensor Networks

Part A: Course Overview

Course Title: Wireless Sensor Networks

Credit Points: 12.00

Course Code




Learning Mode

Teaching Period(s)


City Campus


125H Electrical & Computer Engineering


Sem 2 2011,
Sem 2 2012,
Sem 2 2013,
Sem 2 2014,
Sem 2 2015,
Sem 2 2016


City Campus


125H Electrical & Computer Engineering


Sem 2 2011,
Sem 2 2012,
Sem 2 2013,
Sem 2 2014,
Sem 2 2015,
Sem 2 2016

Course Coordinator: Dr Jidong Wang

Course Coordinator Phone: +61 3 9925 5306

Course Coordinator Email:

Course Coordinator Location: 10.10.11

Pre-requisite Courses and Assumed Knowledge and Capabilities

You are required to have successfully completed EEET2096 Embedded System Design and Implementation and EEET2290 Network Engineering or equivalent. This is not an enforced pre-requisite.

It will be assumed that you have C/C++ programming experience and have fundamental knowledge of TCP/IP networks.

Course Description

A wireless sensor network (WSN) generally consists of compact low power sensors, which collect information and pass the information via wireless networks to achieve a high level of desired monitoring and control in coordinated manners. WSN applications can be found in areas such as environmental monitoring, smart energy systems, battle field surveillance, home automation, medical monitoring, mobile computing, etc. WSN has integrated network engineering, embedded system engineering and sensor technology.

This course covers fundamentals of wireless network technology and distributed sensor networks. After completing this course you should understand the principles of WSN and be able to design and maintain WSNs.

Contents of the course

  • Sensor technology and WSN applications review
  • Wireless technology for distributed sensor networks
  • Clustering techniques in WSN
  • Routing in WSN: AODV, DSR
  • WSN security: principles and protocols
  • WSN security: key management
  • Industrial WSN protocols: ZigBee
  • Networked embedded systems: from chip to system
  • WSN network design and implementation
  • Network support and management
  • WSN performance and introduction of WSN simulation

Objectives/Learning Outcomes/Capability Development

At undergraduate level this course develops the following Program Learning Outcomes of the Bachelor of Engineering (Honours):

     1.3 In-depth understanding of specialist bodies of knowledge within the engineering discipline.
     2.1 Application of established engineering methods to complex engineering problem solving.
     2.2 Fluent application of engineering techniques, tools and resources

At postgraduate level this course develops the following Program Learning Outcomes of the Master of Engineering:

  • High levels of technical competence in the field
  • Be able to apply problem solving approaches to work challenges and make decisions using sound engineering methodologies

On completion of this course you should be able to:

  1. Apply knowledge of wireless sensor networks(WSN) to various application areas.
  2. Design and implement WSN.
  3. Conduct performance analysis of WSN and manage WSN.
  4. Formulate and solve problems creatively in the area of WSN.

Overview of Learning Activities

Student Learning occurs through the following experiences and evaluation processes:

  • Lectures or workshops that provide guided learning of key topics.
  • Self paced learning using reference material as a guide.
  • Laboratory based assignments and a mini project to explore specific topics in depth.

Laboratory practice based assignments are used to assess the concept understanding and basic skill of WSN design.

The mini project is on a system design of a WSN and familiarization of WSN simulation tools.

Final exam is for the overall assessment of WSN concepts and core WSN issues.

Overview of Learning Resources

You will be able to access course information and learning materials through RMIT University’s online systems.

Lists of relevant reference texts, resources in the library and freely accessible Internet sites will be provided.

You will also use state-of-the-art laboratory equipment and computer software within the School in the laboratory practice.

Overview of Assessment

☒ This course has no hurdle requirements.
☐ All hurdle requirements for this course are indicated clearly in the assessment regime that follows, against the relevant assessment task(s) and all have been approved by the College Deputy Pro Vice-Chancellor (Leaning & Teaching).

  • Laboratory Based Assignments
  • A Mini Project
  • An Examination

Assessment tasks

Assessment Task 1: Laboratory practices ( Demo and assignments)
Weighting 20%
This assessment task supports CLOs 1,2,4

Assessment Task 2: Mini-project
Weighting 30%
This assessment task supports CLOs 2,3,4

Assessment Task 3: Final Exam
Weighting 50%
This assessment task supports CLO 1,2,4