Publications
Conferences and Workshops
Experiences with a High-Fidelity Wireless Building Energy Auditing Network [pptx]
Xiaofan Jiang, Minh Van Ly, Jay Taneja, Prabal Dutta, and David Culler
Proceedings of the Seventh ACM Conference on Embedded Networked Sensor Systems (SenSys’09), Nov. 4-6, 2009. To appear.
Design and Implementation of a High-Fidelity AC Metering Network [pptx]
Xiaofan Jiang, Stephen Dawson-Haggerty, Prabal Dutta, and David Culler
The 8th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN’09) Track on Sensor Platforms, Tools, and Design Methods (SPOTS ‘09), Apr. 2009.
An Architecture for Local Energy Generation, Distribution, and Sharing
Mike M. He, Evan M. Reutzel, Xiaofan Jiang, Randy H. Katz, Seth R. Sanders, David E. Culler, Ken Lutz
IEEE Conference on Global Sustainable Energy Infrastructure (Energy2030′08), Nov. 17 –18, 2008.
A Building Block Approach to Sensornet Systems
Prabal Dutta, Jay Taneja, Jaein Jeong, Xiaofan Jiang, and David Culler
In Proceedings of the Sixth ACM Conference on Embedded Networked Sensor Systems (SenSys’08), Nov. 5-7, 2008.
Design and Analysis of Micro-Solar Systems for Wireless Sensor Networks
Jaein Jeong, Xiaofan Jiang and David Culler
The Fifth International Conference on Networked Sensing Systems (INSS 2008), Kanazawa, Japan June 2008
The Effect of Link Churn on Wireless Routing
Stephen Dawson-Haggerty, Jorge Ortiz, Xiaofan Jiang and David E. Culler
Technical Report No. UCB/EECS-2008-109, EECS Department, University of California, Berkeley, 2008
An Architecture for Energy Management in Wireless Sensor Networks
Xiaofan Jiang, Jay Taneja, Jorge Ortiz, Arsalan Tavakoli, Prabal Dutta, Jaein Jeong, David Culler, Philip Levis, Scott Shenker
International Workshop on Wireless Sensor Network Architecture (WSNA’07), Apr. 2007.
Micro Power Meter for Energy Monitoring of Wireless Sensor Networks at Scale
Xiaofan Jiang, Prabal Dutta, David Culler, Ion Stoica
The Sixth International Conference on Information Processing in Sensor Networks (IPSN’07) Track on Sensor Platforms, Tools, and Design Methods (SPOTS ‘07), Apr. 2007.
Perpetual Environmentally Powered Sensor Networks [ppt]
Xiaofan Jiang, Joseph Polastre, David Culler
The Fourth International Conference on Information Processing in Sensor Networks: Special track on Platform Tools and Design Methods for Network Embedded Sensors (IPSN/SPOTS), April 25-27, 2005
Received best paper award
Exploiting the Capture Effect for Collision Detection and Recovery
Kamin Whitehouse, Alec Woo, Fred (Xiaofan) Jiang, Joseph Polastre, David Culler
The Second IEEE Workshop on Embedded Networked Sensors (EmNetS-II), May 30-31, 2005
The Effects of Ranging Noise on Multi-Hop Localization: An Empirical Study
Kamin Whitehouse, Chris Karlof, Alec Woo, Fred (Xiaofan) Jiang, David Culler
The Fourth International Conference on Information Processing in Sensor Networks, April 25-27, 2005
Sensor Field Localization: a deployment and empirical analysis
Kamin Whitehouse, Fred (Xiaofan) Jiang, Alec Woo, Chris Karlof, David Culler
UC Berkeley Technical Report UCB//CSD-04-1349, April 9, 2004.
Master Thesis
High-Fidelity Power Metering and Run-Time Energy Management in Wireless Sensor Networks
Completed in fall of 2007
Recent Talks
Wireless Building Energy Monitoring and LoCal: an Intelligent Power Network [pdf]
Microsoft Research Asia, Beijing, China
Ph.D. Qualifying Examination [pdf]
Date: 2008/12
Committee: David Culler, Randy Katz (chair), Seth Sanders, and Arun Majumdar
Class Projects
Capture Sensing Simultaneous Access [Poster]
Xiaofan Jiang
Using the Capture effect to increase spatial reuse and network bandwidth by allowing weaker captured nodes to simultaneously transmit in the presence of a stronger capturing node.
Dynamic Spring Force Localization [pdf]
Xiaofan Jiang, Dima Ryazanov, and Jorge Ortiz
RSSI based localization by modeling nodes as particles connected by a network of springs.
Detection of Pigs in Heat [ppt]
Zhangxi Tan and Xiaofan Jiang
On-line detection of when sows enter heat-period using 3-axis accelerometer readings. A combination of machine learning techniques, such as PCA anomaly detection and frequency analysis, are used to filter the signals.
