Student research opportunities

Energy Management and Rate Allocation in Renewable Wireless Sensor Networks

Project Code: CECS_820

This project is available at the following levels:
CS single semester, Honours, Summer Scholar, Masters, PhD

Keywords:

renewable energy, wireless sensor networks, temporal-spatial data correlation, energy replenishment, scheduling algorithm. routing protocol design, remote environmental monitoring

Supervisor:

Assoc Professor Weifa Liang

Outline:

Wireless sensor networks have been widely deployed in habitat monitoring, structural health monitoring and environmental sensing. As these applications may require deployment in hard-to-reach areas, it is critical to ensure that such networks can operate unattended for long periods. However, the lack of easy access to a continuous power source and the limited lifetime of batteries have hindered the wide-scale deployment of such networks, because the replacement of batteries is costly and sometimes dangerous
(e.g. networks used to monitor a nuclear disaster site or volcanic eruption).

A viable solution to this problem is allowing sensor nodes to harvest renewable energy, such as solar energy, wind energy, vibration energy, and so on, from their surrounding environments. However, the time-varying characteristics of renewable energy sources poses significant challenges in the design of sensor networks with energy-harvesting abilities (or energy-harvesting sensor networks), particularly in energy management and optimal rate allocation for high-quality sensing data collection.

Goals of this project

This project aims to develop practical but efficient solutions for high-quality data extraction from all the nodes in the presence of renewable energy sources. It will focus on designing efficient algorithms that maximise the quality of collected data. The developed algorithms will be implemented and evaluated in a network simulator.

Requirements/Prerequisites

* Very good skill in one of the programing languages like C/C++ or Java, Matlab.

* excellent background in algorithm design and analysis (has done COMP3600 at least).

* work hard and willing to learn

Contact: