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Research Abstracts Online
January 2008 - March 2009

University of Minnesota Twin Cities
Institute of Technology
Department of Computer Science and Engineering

PI: Tian He

Achieving Balanced and Flexible Military Surveillance at Scale

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 work is to support the next generation of extremely large-scale military surveillance using WSNs. This 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 the multi-dimensional resource constraints, such as limited power, bandwidth, computation, and memory, available in physical sensor devices. The researchers are using multi-objective optimization, which requires extensive computation, to exploit this high-dimensional design space. This task is extremely costly, especially in wireless sensor networks, due to two main 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 use of MSI’s computational capabilities.

Group Members

Chi Yin Chow, Graduate Student
Yu Gu, Graduate Student
Joengmin Hwang, Graduate Student
Jaechoon Jeong, Graduate Student
Qingquan Zhang, Graduate Student
Ziguo Zhong, Graduate Student
Ting Zhu, Graduate Student