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Energy Efficient Processing in IoT Exploiting Renewable Energy

   Faculty of Engineering and Physical Sciences

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  Dr T El-Gorashi, Prof J Elmirghani  Applications accepted all year round  Competition Funded PhD Project (Students Worldwide)

About the Project

The emissions attributed to communication networks continue to grow with growth in traffic. Currently ICT has a carbon footprint that is comparable to the global aviation industry. Unlike aviation whose growth is almost flat, the traffic in ICT networks currently grows at 30% - 40% per year. This means that traffic doubles every two years, and is project to increases by factors of 30x and 1000x in 10 years and 20 years, respectively. A number of approaches have been developed to improve the energy efficiency of communication networks and this research direction has been successful with University of Leeds playing a major role in GreenTouch and its recommendations and the resultant IEEE standards.

The Internet of Things (IoT) has grown in importance in a very wide range of applications in healthcare, vehicular, smart cities and manufacturing. Massive amounts of data are generated and have to be processed to extract knowledge and value from the data. This increases the carbon footprint of these IoT applications.

Further reduction in the carbon footprint of communication networks is possible if the non-renewable energy sources are replaced by renewable energy sources. A key challenge is that renewable energy sources such as wind energy sources and solar energy sources are characterised by their distributed generation and intermittent nature, which create challenges in employing these sources to power communication and processing networks. Employing renewable energy sources in communication networks calls for the efficient use of the power generated and effective planning to minimise the non-renewable energy consumption during low renewable energy generation.

We will treat, for the first time, the lack in renewable energy at a given node at a given point in time as a form of node failure. We will therefore introduce reliability theory to model these situations making use of the mean time to failure (mean time during which there is useful renewable energy generation) and mean time to repair (mean time until useful power generation is resumed) as input measures for the reliability of the wind (in particular) energy sources. We will introduce energy storage to mitigate the adverse impacts of volatility and intermittency of renewable generation and will adapt the rate at which communication nodes send data and processing nodes carry out processing so that these rates are commensurate with the available energy.

Funding Notes

This project is eligible for several funding opportunities, therefore, we recommend that you visit our website for further information.

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