Large-scale Learning and Optimization for Next Generation Wireless Networks
: Network management and configuration is an essential attribute of any wireless network with reliable self-tuning capabilities. However, the cost and overhead of network management has rarely been accounted for from a fundamental limit perspective. In contrast to the current static networking solutions, in the ever-increasingly mobile and large-scale networks of tomorrow the network reconfiguration overhead may not be insignificant; this includes the initial beam alignment, link maintenance, spectrum sensing, packet resizing, etc. Our work aims to provide fundamental limits on the overhead associated with network reconfiguration in general. Our approach relies on fundamental notions in information theory and statistics to quantify the networking overhead and utilizes recent data analytic and machine learning algorithms to develop practical learning/optimization algorithms.
In the first part of the talk, we consider the problem of reliably and quickly searching for a parameter of interest in a large signal space in face of measurement noise. This problem naturally arises in many practical communications systems such as the directional link establishment and maintenance (beam alignment) as well as spectrum sensing for cognitive radios. We show that, despite the unreliability of observations, by carefully constructing the redundancy, inspired by Shannon's channel coding theorem, the overhead can be kept minimal (and in some settings to grow only logarithmically with the resolution of the search). Furthermore, we characterize the benefit of adaptive processing which in turn provides guidelines for trading off the network performance with computational complexity. In the second part of the talk, we consider an important variant of the search problem: data-driven function optimization. We survey the literature on data-driven function maximization and discuss some existing work as well as open problems in this domain.
Tara Javidi studied electrical engineering at Sharif University of Technology, Tehran, Iran from 1992 to 1996. She received her MS degrees in electrical engineering (systems) and in applied mathematics (stochastic analysis) from the University of Michigan, Ann Arbor, in 1998 and 1999, respectively. She received her Ph.D. in electrical engineering and computer science from the University of Michigan, Ann Arbor, in 2002.
From 2002 to 2004, Tara Javidi was an assistant professor at the Electrical Engineering Department, University of Washington, Seattle. In 2005, she joined the University of California, San Diego, where she is currently a professor of electrical and computer engineering. In 2013-2014, she spent her sabbatical at Stanford University as a visiting faculty. At the University of California, San Diego, Tara Javidi directs the Advanced Networking Science Lab and is an active member of the Centers of Information Theory and Applications, Wireless Communications, Networked Systems, and Integrated Access Network.
Internet Economics: Competition and Cooperation
: The issue of Network Neutrality has ignited considerable public debate
recently. While the term and much of the discussion originated in the
legal community, we started looking at it from an engineering and
networking perspective a few years ago. We employed the lens of
cooperative game theory and a careful modeling of the Internet
including the topology, peering relationships and protocols used on
the Internet. Our primary conclusion is that Network Neutrality should
be expressed in terms of how you treat competition, not in how you
treat packets and we proposed a definition of Network Neutrality that
We present some of our results including our prediction back in 2008
of a rise in paid peering (last year Netflix signed paid peering
arrangements with all 4 of the top broadband providers in the US),
the inadequacies of the Network Neutrality regulation in the US and
the recent regulations in India and Canada, where they are are consistent
with our definition of Network Neutrality.
Vishal Misra is a Professor in the Department of Computer
Science at Columbia University, with a joint appointment in the
Electrical Engineering Department and an IEEE Fellow. His research emphasis is on
mathematical modeling of networking systems, bridging the gap between
practice and analysis. He served as the Vice-Chair of the Computer
Science Department at Columbia University from 2009 to 2011, and in
2011 he spun out Infinio, a company in the area of datacenter
storage. He is also credited with inventing
live-microblogging at CricInfo, a company he co-founded while a
graduate student at UMass Amherst, predating Twitter by 10
years. CricInfo was later acquired by ESPN and is still the world’s
most popular sports portal.
Vision 2020: Top Technology Trends in Telecom
: The global telecom industry has been undergoing a massive change over the last few years. Large mobile operators are seeing a decline in voice and SMS revenues but data revenues continue to grow strongly. These trends are driven by large-scale rollouts of high-speed 4G networks, increasing availability of affordable smartphones, tablets and other mobile devices, and growing consumer preference for video applications. Fixed-line carriers too are adopting high-speed fiber, copper and wireless access technologies fueling a data deluge in telecom networks. In this talk, we will discuss how telecom infrastructure is evolving to respond to these changes and evaluate the role of new technologies (5G, IoT, SDN) in next-generation telecom networks.
Dr. Kumar Sivarajan is responsible for setting the technology and
product direction for Tejas Networks . Prior to Tejas Networks,
Kumar was an Associate Professor in the Electrical Communication
Engineering Department, at the Indian Institute of Science,
Bangalore . Prior to that he has also worked with the IBM Thomas
J . Watson Research Center , Yorktown Heights, New York . Kumar
is co - author of the textbook `Optical Networks : A Practical
Perspective' published in February 1998 . He is a Fellow of the
Indian National Academy of Engineering, an Associate of the Indian
Academy of Sciences, and a recipient of the Swarnajayanti
Fellowship from the Department of Science and Technology, and the
2004 Global Indus Technovator Award from the India Business Club
at the Massachusetts Institute of Technology . He is also a
recipient of the Institute of Electrical and Electronics Engineers
Inc , Fortescue Fellowship and Institute of Electrical and
Electronics Engineers Inc , Baker Prize Paper Award . Kumar holds
a Bachelor’s Degree in Technology in Electrical Engineering from
the Indian Institute of Technology, Madras and a Doctorate from
the California Institute of Technology .