2009/12/12 by Feng Xia, Xia, Feng, Zhenzhen Xu +8
Computer Science · Engineering · #Distributed #Energy Efficient Wireless Sensor Networks #Energy Harvesting in Wireless Networks #FOS: Computer and information sciences #Networking and Internet Architecture (cs.NI) #Parallel #Wireless Body Area Networks #and Cluster Computing (cs.DC) #cs.DC #cs.NI
paper · pdf · doi:10.48550/arxiv.0912.2430
To appear in The Int Workshop on Ubiquitous Body Sensor Networks (UBSN), in conjunction with the 5th Annual Int Wireless Internet Conf (WICON), Singapore, March 2010
arxiv created 2009/12/12 · openalex publication_date 2009/12/12 · arxiv updated 2010/01/07 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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 PID (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.