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11/03(Fri.) No CSIE Seminar Speech.Move to 11/06(Mon)afternoon,in Lecture I A127(1F)-English Lecture

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Principal invites Prof. Edward Coyle, IEEE Fellow (Edward J. Coyle, John B. Peatman Distinguished Professor and GRA Eminent Scholar) from School of Electrical and Computer Engineering,Georgia Institute of Technology, to share his research results.

Introduction to the speaker：

Prof. Edward J. Coyle
 John B. Peatman Distinguished Professor of ECE, Gatech
Founding Director of the VIP Consortium
Director of the Arbutus Center for the Integration of Research and Education
Georgia Research Alliance Eminent Scholar
Edward J. Coyle received his B.S. degree in Electrical Engineering from the University of Delaware in 1978 and the Ph.D. degree in Electrical Engineering and Computer Science from Princeton University in 1982. From 1982 through 2007, he was a faculty member at Purdue University, where he served at various times as Assistant Vice Provost for Research, co-director of the Center for Wireless Systems and Applications, and co-founder of both the Vertically Integrated Projects (VIP) Program and the Engineering Projects in Community Service (EPICS) program. During the 2006-07 academic year, he was the Kenan Trust Visiting Professor at Princeton University.
Dr. Coyle joined Georgia Tech in January 2008. At Tech he is the John B. Peatman Distinguished Professor of ECE, the Director of the Arbutus Center for the Integration of Research and Education, and a Georgia Research Alliance Eminent Scholar. He is also the Founding Director of the VIP Consortium, a group of 15 universities that focus on the growth and dissemination of the VIP program. The Consortium recently received a $5M grant from the Leona M. and Harry B. Helmsley Charitable Trust to help achieve systemic reform of STEM education.

 

Time: 14:00~16:00

Localtion: Lecture Hall I(A127), 1st floor of Science & Engineering Building II.

Language: English

 

Topic：

Optimal Clustered Architectures for the Collection of Data in Large-Scale IoT Applications

 

Abstract：

In large-scale Internet of Things (IoT) applications, making good decisions requires both fast and energy-efficient approaches to gathering data. This is a significant challenge when the data that must be gathered is spread across thousands of devices. To demonstrate this, we consider algorithms for gathering data from the smartphones of thousands of people at large events, such as a football game. When aggregation of data is possible, clustered communication architectures for gathering that data are appropriate. We thus derive multi-level clustering algorithms that minimize the energy expended when different levels of aggregation are required at different levels of the architecture. We also show how data can be gathered in a time-efficient manner in a single cluster by only collecting the most reliable data. The next step in this research must be to determine the most energy efficient approach to data collection when there is a fixed time to gather data from all clusters, not just one cluster.