TY - JOUR T1 - Process Modeling for Soil Moisture Using Sensor Network Data . JF - Statistical Methodology (Special issue on modern statistical methods in ecology) Y1 - 2014 A1 - Ghosh,S A1 - Bell,DM A1 - Clark,JS A1 - Gelfand,AE A1 - Flikkema,P VL - 12 N1 - [Original String]:Ghosh S, Bell DM, Clark JS, Gelfand AE, and Flikkema P. 2014. Process Modeling for Soil Moisture Using Sensor Network Data . Statistical Methodology (Special issue on modern statistical methods in ecology)12: 99-112. ER - TY - CONF T1 - Progressive coding and iterative source-channel decoding in wireless data gathering networks . T2 - Proceedings of 2011 IEEE Global Telecommunications Conference Y1 - 2011 A1 - Li,C A1 - PG Flikkema A1 - Howard,SL JF - Proceedings of 2011 IEEE Global Telecommunications Conference T3 - Proceedings of 2011 IEEE Global Telecommunications Conference PB - IEE GLOBECOM CY - Houston, TX, USA N1 - [Original String]:Li C, Flikkema PG, Howard SL. 2011. Progressive coding and iterative source-channel decoding in wireless data gathering networks . Proceedings of 2011 IEEE Global Telecommunications Conference, GLOBECOM 2011; Dec 5-9; Houston. ER - TY - Generic T1 - Prospector: Multiscale Energy Measurement of Networked Embedded Systems with Wideband Power Signals T2 - Proceedings of 12th IEEE International Conference on Computational Science and Engineering Y1 - 2009 A1 - Yamamoto,KR A1 - PG Flikkema AB -

Today鈥檚 wirelessly networked embedded systems underlie a vast array of electronic devices, performing computation,communication, and input/output. A major design goal of these systems is energy efficiency. To achieve this goal, these systems are based on processors with numerous power and clock domains, variable clock rates, voltage scaling, and multiple hibernation states. These processors are designed into systems with sophisticated wireless transceivers and a diverse array of off-chip peripherals, and are linked through regulators to increasingly complexenergy supplies. As a result, modern networked embeddedsystems are characterized by myriad power consumption statesand significant power signal transients. Moreover, their power demands are multiscale in both magnitude and time, combining short bursts of high demand with long intervals of power-sipping sleep states. Thus the power supply signals have wideband spectra. In addition, due to noise, uniform relative precision across magnitude scales requires that measurement time increases with decreasing power. Tools are needed that support modeling, hardware/software optimization, and debugging for energy-centric embedded systems. This paper describes Prospector, an energy data acquisition system architecture for embedded systems thatallows rapid, accurate, and precise assessment of system-level power usage. Prospector uses a distributed control architecture; each component contributes efficiently to control, precision and accuracy, analysis, and visualization. It is based on computer-based control of multimeters to maximize accuracy, precision,铿俥xibility, and minimize target system overhead. Experimental results for a prototype Prospector system with a contemporary 16-bit ultra-low power microcontroller show that it can effectivelymeasure power over the extreme time and magnitude scales found in today鈥檚 embedded systems.

JF - Proceedings of 12th IEEE International Conference on Computational Science and Engineering T3 - Proceedings of 12th IEEE International Conference on Computational Science and Engineering; PB - IEEE CY - Vancouver, Canada VL - 2 UR - http://dl.acm.org/citation.cfm?id=1633490 ER - TY - CONF T1 - The precision and energetic cost of snapshot estimates in wireless sensor networks . T2 - Proceedings of 11th Annual IEEE Symposium on Computing and Communications 2006 Y1 - 2006 A1 - PG Flikkema JF - Proceedings of 11th Annual IEEE Symposium on Computing and Communications 2006 T3 - Proceedings of 11th Annual IEEE Symposium on Computing and Communications 2006 PB - IEEE ISCC ’06 CY - Cagliari Italy N1 - [Original String]:Flikkema PG. 2006.The precision and energetic cost of snapshot estimates in wireless sensor networks . Proceedings of 11th Annual IEEE Symposium on Computing and Communications 2006 (IEEE ISCC ’06); 2006 June 26-29; Cagliari, Italy; p 603-608. ER -