Making
Dense Networks Smarter with Randomized Network
Coding and Distributed Signal Processing
By
-
Prof.
Kannan Ramchandran
Professor,
Department of Electrical Engineering and Computer
Science, University of California at Berkeley
|
Date:
Nov 26, 2008 (Wednesday) |
Time:
2:30pm - 3:30pm |
Venue:
Rm. 1009, William M.W. Mong Engineering Building,
CUHK |
Abstract
:
The
proliferation of wireless sensor and ad hoc networks
has highlighted the systems challenge of robustly
scaling these systems. The need for robust scalability
naturally imposes constraints on individual node resources
and reliability. Yet, as a collection, can these nodes
be made to overcome their individual limitations in
realizing a quantifiably efficient network by deriving
strength from numbers? Can this further be done with
little or no centralized control or global co-ordination?
We will explore this vision in some concrete large-scale
network settings by emphasizing a minimalistic, distributed
and randomized approach to network coding and signal
processing. The scenarios we explore, time permitting,
include: (i) decentralized networked and peer-to-peer
storage; (ii) reliable multi-hop communication; and
(iii) distributed multi-resolution representation.
Biography
:
Kannan
Ramchandran (Ph.D.93, Columbia University) is a Professor
of Electrical Engineering and Computer Science at
the University of California at Berkeley, where he
has been since 1999. Prior to that, he was with the
University of Illinois at Urbana-Champaign from 1993
to 1999, and was at AT&T Bell Laboratories from 1984
to 1990. His current research interests include distributed
signal processing algorithms for wireless sensor and
ad hoc networks, multimedia and peer-to-peer networking,
multi-user information and communication theory, and
wavelets and multi-resolution signal and image processing.
Prof. Ramchandran is a Fellow of the IEEE. His research
awards include the Elaihu Jury award for the best
doctoral thesis in the systems area at Columbia University,
the NSF CAREER award, the ONR and ARO Young Investigator
Awards, two Best Paper awards from the IEEE Signal
Processing Society, a Hank Magnuski Scholar award
for excellence in junior faculty at the University
of Illinois, and an Okawa Foundation Prize for excellence
in research at Berkeley. He is a Fellow of the IEEE.
He has published extensively in his field, holds 8
patents, serves as an active consultant to industry,
and has held various editorial and Technical Program
Committee positions. |