You can manage bookmarks using lists, please log in to your user account for this.
Media type:
Electronic Conference Proceeding;
Text
Title:
Energy Efficient Video Compression for Wireless Sensor Networks
Contributor:
Ahmad, Junaid Jameel
[Author];
Khan, Hassan A.
[Author];
Khayam, Syed Ali
[Author]
imprint:
KOPS - The Institutional Repository of the University of Konstanz, 2009
Language:
English
DOI:
https://doi.org/10.1109/CISS.2009.5054795
Origination:
Footnote:
Diese Datenquelle enthält auch Bestandsnachweise, die nicht zu einem Volltext führen.
Description:
Wireless video sensor networks are anticipated to be deployed to monitor remote geographical areas. To save energy in bit transmissions/receptions over a video sensor network, the captured video content needs to be encoded before its transmission to the base station. However, video encoding is an inherently complex operation that can cause a major energy drain at battery-constrained sensors. Thus a systematic evaluation of different video encoding options is required to allow a designer to choose the most energy-efficient compression technique for a given video sensing application scenario. In this paper, we empirically evaluate the energy efficiencies of predictive and distributed video coding paradigms for deployment on real-life sensor motes. For predictive video coding, our results show that despite its higher compression efficiency, inter video coding always depletes much more energy than intra coding. Therefore, we propose to use image compression based intra coding to improve energy efficiency in the predictive video coding paradigm. For distributed video coding, our results show that the Wyner-Ziv encoder has consistently better energy efficiency than the PRISM encoder. We propose minor modifications to PRISM and Wyner-Ziv encoders which significantly reduce the energy consumption of these encoders. For all the video encoding configurations evaluated in this paper, our results reveal the counter-intuitive and important finding that the major source of energy drain in WSNs is local computations performed for video compression and not video transmission. ; published