Cross-Layer Design to Optimize Power in Video Sensor Networks - Arar, Aisha
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Wireless Video Sensor Network (WVSN) is one type of Wireless Sensor Network (WSN), where each sensor is equipped with a camera component to capture videos, in addition to a processing component to process the captured videos before transmission. Many applications of WVSNs are widely used, such as surveillance applications that monitor and prevent harmful events, environmental tracking, and health monitoring applications.This work studies the problem of minimizing the total power consumption in a clustered based WVSN by proposing a cross-layer design to optimize the encoding power, the…mehr

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Produktbeschreibung
Wireless Video Sensor Network (WVSN) is one type of Wireless Sensor Network (WSN), where each sensor is equipped with a camera component to capture videos, in addition to a processing component to process the captured videos before transmission. Many applications of WVSNs are widely used, such as surveillance applications that monitor and prevent harmful events, environmental tracking, and health monitoring applications.This work studies the problem of minimizing the total power consumption in a clustered based WVSN by proposing a cross-layer design to optimize the encoding power, the transmission power, and the source rate at each sensor node. The resource allocation is incorporated into a minimization problem, which takes into account the video signal distortion due to compression and packet losses in the wireless channel while trying to allocate network resources amongst multiple video sensors, such that the total power consumed in both compression and communication is minimized. For efficient communication, energy harvesting capability is added, where sensor nodes in the network are allowed to use renewable energy sources to contribute in green communication.
Autorenporträt
Aisha Arar received her B.Sc degree in computer engineering with honors from Qatar University in 2008. She received her M.Sc. in Computing from Qatar University in 2014. She worked as an applications engineer on developing and testing innovative wireless solutions. Her research interests primarily in Energy-Efficient Cross-layer design for WSNs.