University of Minnesota
University Relations

Minnesota Supercomputing Institute

Log out of MyMSI

Research Abstracts Online
January 2010 - March 2011

Main TOC ...... Next Abstract

University of Minnesota Twin Cities
College of Science and Engineering
Department of Computer Science and Engineering

PI: Tian He

Building Optimized Sensor Networks

Wireless Sensor Networks (WSNs) have a large confluence of characteristics that make them unique both in terms of their technical requirements and in potential applications. The objective of this research is to support the next generation of extremely large-scale military surveillance, using WSNs. The project is aimed at developing a balanced and flexible architecture and a physical implementation. The main challenge is how to reconcile and/or trade off concurrent performance goals through a cross-layer design, subject to multi-dimensional resource constraints, such as the limited power, bandwidth, computation and memory, available in physical sensor devices. To realize their objectives, these researchers are performing multi-objective optimization, which requires extensive computation to exploit this high-dimensional design space. This task is extremely costly, especially in WSNs, primarily for two reasons. First, the realization of realistic sensing and wireless communication patterns can be orders of magnitude more expensive than in high-level simulations. Second, the aggregated behaviors of a sensor system can only be revealed accurately after the simulation reaches a certain scale. These combined requirements necessitate the high computation capability available from MSI.

Group Members

Yongle Cao, Graduate Student
Pengpeng Chen, Undergraduate Student
Liangyin Chen, Graduate Student
Chi Yin Chow, Graduate Student
Yu Gu, Graduate Student
Shuo Guo, Graduate Student
Joengmin Hwang, Graduate Student
Jaechoon Jeong, Graduate Student
Fulong Xu, Graduate Student
Qingquan Zhang, Graduate Student
Ziguo Zhong, Graduate Student
Ting Zhu, Graduate Student