TY - GEN

T1 - Resilient control in long-range sensor and actuator networks

AU - Linares, Jose

PY - 2017

Y1 - 2017

N2 - This thesis will provide an insight on how weather factors such as temperature, humidity and air pressure affects radio links and use this body of knowledge to better understand how to mitigate unnecessary radio switching to take place and then use this knowledge to suggest ways of developing a Link Quality Estimator that utilize online weather data to be able to conduct smart link switching. In the context of this thesis, we focus on the case study of a water utility company as these entities are under increasing economic and environmental pressures to optimise their infrastructure, in order to save energy, mitigate extreme weather events, and prevent water pollution. One promising approach consists in using smart systems. However, a smart infrastructure requires reliable communication links which are difficult to provide. In particular, communication links that are distributed and geographically located in rural areas are highly affected by changing weather conditions, hence efficient control of these distributed hosts requires robust communications. Multiple communication transceivers are used to mitigate this issue and to enable nodes to switch to reliable links. Short-term link quality estimators are used to decide which link to use which often leads to the situation where a link switch is initiated which does not prove helpful in the long term. It is not beneficial to switch a link and associated routing for only a brief duration hence we conduct test bed experiments to better understand the relationships between the radio links and weather factors and use this body of data to devise a LQE that can use this data and then make a smart choice based on this data which reduces switching costs.

AB - This thesis will provide an insight on how weather factors such as temperature, humidity and air pressure affects radio links and use this body of knowledge to better understand how to mitigate unnecessary radio switching to take place and then use this knowledge to suggest ways of developing a Link Quality Estimator that utilize online weather data to be able to conduct smart link switching. In the context of this thesis, we focus on the case study of a water utility company as these entities are under increasing economic and environmental pressures to optimise their infrastructure, in order to save energy, mitigate extreme weather events, and prevent water pollution. One promising approach consists in using smart systems. However, a smart infrastructure requires reliable communication links which are difficult to provide. In particular, communication links that are distributed and geographically located in rural areas are highly affected by changing weather conditions, hence efficient control of these distributed hosts requires robust communications. Multiple communication transceivers are used to mitigate this issue and to enable nodes to switch to reliable links. Short-term link quality estimators are used to decide which link to use which often leads to the situation where a link switch is initiated which does not prove helpful in the long term. It is not beneficial to switch a link and associated routing for only a brief duration hence we conduct test bed experiments to better understand the relationships between the radio links and weather factors and use this body of data to devise a LQE that can use this data and then make a smart choice based on this data which reduces switching costs.

M3 - Master's Thesis

PB - Lancaster University

ER -