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Designing Efficient Algorithms for Large Communication Networks

Event Date: May 11, 2010
Speaker: Dr. Jian Ni
Speaker Affiliation: University of Illinois at Urbana-Champaign
Sponsor: Communications, Networking, Signal & Image Processing
Time: 2:00 PM
Location: MSEE 239
Contact Name: Prof Xiaojun Lin
Contact Phone: (765) 494-0626
Contact Email:

As modern communication networks continue to grow in size and complexity, analysis and design of these networks will become even more challenging. Over the last century physicists and biologists have developed many powerful tools to study the complex systems and networks in their fields. In this talk I will show how these tools can help us design efficient algorithms for large communication networks.

Dr. Jian Ni is a Post-doctoral Researcher with the Coordinated Science Laboratory, University of Illinois at Urbana-Champaign. He received his B. Eng. Degree in automation from Tsinghua University, Beijing, in 2001, his M.Phil. degree in electrical and electronic engineering from HKUST, Hong Kong, in 2003, and his Ph.D. degree in electrical engineering from Yale University, New Haven, in 2008. His research interests include developing theory and algorithms for analysis, measurement, inference, and optimization of communication networks and large-scale distributed systems.












Topology in the Internet. I will present a general framework for designing network inference

algorithms using ideas and tools from phylogenetic inference in evolutionary biology.

Based on the framework I will introduce distance-based inference algorithms that are both

computationally efficient and consistent. In the second part of the talk we will consider the

design of distributed scheduling algorithms for wireless networks. I will present a

discrete-time CSMA algorithm which is based on a generalization of the so-called Glauber

dynamics from statistical physics. The algorithm achieves the maximum throughput

in multi-hop wireless networks with a fully distributed implementation.