Speaker
Professor Rong Zheng
Mc Master University
Title
Sequential learning in wireless monitoring
Abstract
Passive
monitoring
is
a
technique
where
a
dedicated
set
of
hardware devices,
called
sniffers,
are
used
to
monitor
activities
in
wireless networks.
These
devices
capture
transmissions
of
wireless
devices
or
activities
of
interference
sources
in
their
vicinity,
and
store
packet
level
or
PHY
layer
information
in
trace
files,
which
can
be
analyzed distributively
or
at
a
central
location.
Since
most,
if
not
all,
infrastructure
networks
utilize
multiple
contiguous
or
non-contiguous
channels
or
bands,
an
important
issue
is
to
determine
which
set
of
frequency
bands
each
sniffer
operates
on
to
maximize
the
total
amount
of
information
gathered.
In
this
talk,
we
consider
the
problem
of
optimally assigning
p
sniffers
to
K
channels
to
monitor
the
transmission
activities
in
a
multi-channel
wireless
network.
The
activity
of
users
is
initially
unknown
to
the
sniffers
and
is
to
be
learned
along
with channel
assignment
decisions.
We
devise
efficient
sequential
learning approaches
and
address
practical
constraints
including
channel
switching
time,
computation
costs
and
non-stationary
network
conditions.
Speaker Biography
Rong Zheng received her Ph.D. degree from Dept. of Computer Science, University of Illinois at Urbana-Champaign and earned her M.E. and B.E. in Electrical Engineering from Tsinghua University, P.R. China. She is presently an associate professor in the Department of Computing and Software, McMaster University. She was with the University of Houston from 2004 to 2012.
Rong Zheng's research interests include network monitoring and diagnosis, cyber physical systems, and mobile computing. She is the recipient of the US National Science Foundation CAREER Award in 2006, and University of Houston research excellence award in 2010. She served on the technical program committees of several leading networking conferences, and was the program co-chair of WASA'12 and CPSCom'12.