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Prediction-based data transmission for energy conservation in wireless body sensors

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5 Author(s)
Xia Feng ; School of Software, Dalian University of Technology, Dalian 116620, China ; Xu Zhenzhen ; Yao Lin ; Sun Weifeng
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Wireless body sensors are becoming popular in healthcare applications. Since they are either worn or implanted into human body, these sensors must be very small in size and light in weight. The energy consequently becomes an extremely scarce resource, and energy conservation turns into a first class design issue for body sensor networks (BSNs). This paper deals with this issue by taking into account the unique characteristics of BSNs in contrast to conventional wireless sensor networks (WSNs) for e.g. environment monitoring. A prediction-based data transmission approach suitable for BSNs is presented, which combines a dual prediction framework and a low-complexity prediction algorithm that takes advantage of PIF (proportional-integral-derivative) control. Both the framework and the algorithm are generic, making the proposed approach widely applicable. The effectiveness of the approach is verified through simulations using real-world health monitoring datasets.

Published in:

Wireless Internet Conference (WICON), 2010 The 5th Annual ICST

Date of Conference:

1-3 March 2010