OS-Based Sensor Node Platform and Energy Estimation Model for Health-Care Wireless Sensor Networks

Francisco Rincón, Computer Architecture and Automation Department (DACYA), Complutense University of Madrid (UCM), Madrid, Spain

Abstract: Accurate power and performance figures are critical to assess the effective design of possible sensor node architectures in Body Area Networks (BANs) since they operate on limited energy storage. Therefore, accurate power models and simulation tools that can model real-life working conditions need to be developed and validated with real platforms. In this talk I present a sensor node platform designed for health-care applications and a validated simulation model based on event-driven operating system simulation that can be used to accurately analyze performance and power consumption in BANs composed of multiple nodes. Thus, this model can be employed to tune the node architecture and communication layer for different working conditions, applications and topologies of BANs. The proposed simulation model has been validated on different real-life applications and working conditions. The results show variations of less than 4% between the presented simulation framework and measurements in the final platforms.

About the speaker: Francisco Javier Rincón Vallejos received his MS degree in Computer Science from Complutense University of Madrid (UCM), Spain, in 2006. Since 2006 he is a PhD student at the Computer Architecture and Automation Department (DACYA) of UCM. Currently he is a visiting PhD student at the Integrated Systems Laboratory (LSI) at Ecole Polytechnique Fédérale de Lausanne (EPFL), Switzerland. His research interests are focused on power modeling and optimization of Wireless Sensor Networks for health-care applications.