DSP Processors Hit the Mainstream
Computer
LCN '04 Proceedings of the 29th Annual IEEE International Conference on Local Computer Networks
Energy Scavenging for Mobile and Wireless Electronics
IEEE Pervasive Computing
Eco: an ultra-compact low-power wireless sensor node for real-time motion monitoring
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Wearable wireless sensor network to assess clinical status in patients with neurological disorders
Proceedings of the 6th international conference on Information processing in sensor networks
Requirements and design spaces of mobile medical care
ACM SIGMOBILE Mobile Computing and Communications Review
Exploring the Processor and ISA Design for Wireless Sensor Network Applications
VLSID '08 Proceedings of the 21st International Conference on VLSI Design
Proceedings of the 2nd International Workshop on Systems and Networking Support for Health Care and Assisted Living Environments
Challenges of implementing cyber-physical security solutions in body area networks
BodyNets '09 Proceedings of the Fourth International Conference on Body Area Networks
To hop or not to hop: network architecture for body sensor networks
SECON'09 Proceedings of the 6th Annual IEEE communications society conference on Sensor, Mesh and Ad Hoc Communications and Networks
bHealthy: a physiological feedback-based mobile wellness application suite
Proceedings of the 4th Conference on Wireless Health
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Body Sensor Networks (BSNs) consist of sensor nodes deployed on the human body for health monitoring. Each sensor node is implemented by interfacing a physiological sensor with a sensor platform consisting of components such as microcontroller, radio and memory. Diverse needs of BSN applications require customized platform development for optimizing performance. In this paper, we propose a two-phase framework to evaluate the performance of sensor platforms to match a BSN's computation, communication and sensing requirements: 1) Design Space Determination, wherein we investigate salient features of BSN platforms and quantify them as design coordinates through evaluation metrics such as SPSW (Samples Processed per Second per Watt) and EPC (Expected Power Consumption). To measure these metrics for a platform under typical BSN application workloads, we propose BSN-Bench, a benchmarking suite composed of basic tasks that occur in diverse BSN applications. BSNBench enables an accurate profiling of platforms based on the design coordinates; 2) Design Space Exploration, wherein we explore the design space to find the most suitable platform for a given application. We demonstrate the usage of our framework through a case study, where we consider two practical BSN applications and choose suitable platforms for them.