Paradigm shift and continuous enhancement to safety and effectiveness in medical health, has proved a video transmission as a giant and significant leap during an emergency situation. Nevertheless, the energy hungry video encoding and transmission processes and slow progress in battery technologies have become a key and severe problem for the evolution of video technology in WBSNs. So, managing energy during voluminous and variable bit rate (VBR) video transmission in WBSN is a challenging and crucial issue for researchers and engineers. Therefore, the need arose to conduct research on efficient energy management video transmission techniques to overcome the limitations of sensor nodes. In order to address such problem, a novel sustainable energy management algorithm (EMA) is proposed. The proposed algorithm manages encoding and transmission energies and extends lifetime of WBSNs. The experimental results demonstrate that EMA manages and saves energy up to 41.5% in comparison with Baseline algorithm.

Energy management during video transmission in wireless body sensor networks

Fortino, Giancarlo
2017-01-01

Abstract

Paradigm shift and continuous enhancement to safety and effectiveness in medical health, has proved a video transmission as a giant and significant leap during an emergency situation. Nevertheless, the energy hungry video encoding and transmission processes and slow progress in battery technologies have become a key and severe problem for the evolution of video technology in WBSNs. So, managing energy during voluminous and variable bit rate (VBR) video transmission in WBSN is a challenging and crucial issue for researchers and engineers. Therefore, the need arose to conduct research on efficient energy management video transmission techniques to overcome the limitations of sensor nodes. In order to address such problem, a novel sustainable energy management algorithm (EMA) is proposed. The proposed algorithm manages encoding and transmission energies and extends lifetime of WBSNs. The experimental results demonstrate that EMA manages and saves energy up to 41.5% in comparison with Baseline algorithm.
2017
9781509044283
Energy management; VBR; Video Transmission; WBSNs; Computer Networks and Communications; Computer Science Applications1707 Computer Vision and Pattern Recognition; Control and Optimization; Instrumentation
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/269409
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