Research interests: mathematics of communications, combinatorial problems in communication theory and signal processing.
1996-present: AT&T Shannon Laboratory: Member Technical Staff; Department Head, Communications Sciences Research; Distinguished Member of Technical Staff. Adjunct Prof., Columbia University, NY, 2008, 2009.
1989-1996:Texas A&M University, Electrical Engineering, Assistant, Associate Professor, 1989-1996.
This version of the work is reprinted here with permission of IEEE for your personal use. Not for redistribution. The definitive version was published in 2012. , 2013-01-01
{Virtualized cloud-based services can take advantage of statistical
multiplexing across applications to yield significant cost savings. However, achieving similar savings with real-time services can be a challenge. In this paper, we seek to lower a provider's costs for real-time IPTV services through a virtualized IPTV architecture and through intelligent time-shifting of selected services.
Using Live TV and Video-on-Demand (VoD) as examples, we show that we can
take advantage of the different deadlines associated with each service to effectively multiplex these services. We provide a generalized framework for computing the amount of resources needed to support multiple services, without missing the deadline for any service. We construct the problem as an optimization formulation that uses a generic cost function. We consider multiple forms for the cost function (e.g., maximum, convex and concave functions) reflecting the cost of providing the service. The solution to this formulation gives the number of servers needed at different time instants to support these services. We implement a simple mechanism for time-shifting scheduled jobs in a simulator and study the reduction in server load using real traces from an operational IPTV network. Our results show that we are able to reduce the load by $sim24\%$ (compared to a possible $sim31.3\%$ as predicted by the optimization framework). We also show that there are interesting open problems in designing mechanisms that allow time-shifting of load in such environments.}
This version of the work is reprinted here with permission of IEEE for your personal use. Not for redistribution. The definitive version was published in FOURTH INTERNATIONAL CONFERENCE ON COMMUNICATION SYSTEMS AND NETWORKS. , 2012-01-04
{Virtualized cloud-based services can take advantage of statistical multiplexing
across applications to yield significant cost savings to the operator. However,
achieving similar benefits with real-time services can be a challenge. In this
paper, we seek to lower a provider's costs of real-time IPTV services through a
virtualized IPTV architecture and through intelligent time-shifting of service
delivery. We take advantage of the differences in the deadlines associated with
Live TV versus Video-on-Demand (VoD) to effectively multiplex these services.
We provide a generalized framework for computing the amount of resources needed
to support multiple services, without missing the deadline for any service. We
construct the problem as an optimization formulation that uses a generic
cost function. We consider multiple forms for the cost function (e.g., maximum,
convex and concave functions) to reflect the different pricing options. The
solution to this formulation gives the number of servers needed at different time instants to support these
services. We implement a simple mechanism for time-shifting scheduled jobs in a
simulator and study the reduction in server load using real traces from an
operational IPTV network. Our results show that we are able to reduce the load
by $sim24\%$ (compared to a possible $sim31\%$). We also show that there
are interesting open problems in designing mechanisms that allow time-shifting
of load in such environments.}
This version of the work is reprinted here with permission of IEEE for your personal use. Not for redistribution. The definitive version was published in 2012 , 2012-03-21
{In order to manage interference in the K-user interference
channel we study optimal interference aligned solutions
using the Grassmannian distance between the signal and the
interference space as a metric. A locally optimal algorithm to
optimize the Grassmannian distance is described. The proposed
metric and algorithm are validated by an improvement in the
probability of error as compared to the baseline aligned solution.}
This version of the work is reprinted here with permission of IEEE for your personal use. Not for redistribution. The definitive version was published in 2012. , 2012-09-30
{Camera calibration is essential for many applications of computer
vision. However, the process of calibration can be very time
consuming and may require a significant amount of human
intervention. Calibration models traditionally employ a calibration
grid whose four corner points must be marked by hand on a
per-frame basis. Our objective is to develop a technique for
processing these frames rapidly, with as little human intervention
as possible. In this paper, we propose an algorithm to extract the
boundaries of the calibration grid automatically, based on a
spectral analysis of HD (high-definition) video frames. We
compare the accuracy of the intrinsic parameters estimated using
our automatic method with a method that involves hand labeling of
the corner points.}
(c) ACM, 2011. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in IMC 2011, 2011-11-02.
{We investigate how consumers view content using Video on
Demand (VoD) in the context of an IP-based video distribution
environment. Users today can use advanced stream
control functions like skip and replay in addition to play,
fast-forward, rewind, pause etc., to interactively control their
viewing. Such stream control, however, places additional
demands on the distribution infrastructure (servers, network,
and set top boxes) and can be challenging to manage with a
large subscriber base. A model of user-interaction is useful
to provide key insights on their impact on server and bandwidth
requirements, client responsiveness, etc.
We capture user activity in their natural setting of viewing
video at home. We first develop a model for the arrival
process of requests for content. We then develop two stream
control models that accurately capture user interaction. We
show that stream control events can be characterized by a finite
state machine and a sojourn time model, parametrized
for major periods of usage (weekend and weekday). Our
semi-Markov (SM)model for the sojourn time in each stream
control state uses a novel technique based on a polynomial fit
to the logarithm of the Inverse CDF. A second Constrained
model (CM) uses a stick-breaking approach familiar in machine
learning to model the individual state sojourn time
distributions. The SM model seeks to preserve the sojourn
time distribution for each state while the CM model puts a
greater emphasis on preserving the overall session duration
distribution. Using traces across a period of 2 years from
a large-scale operational IPTV environment we validate the
proposed model and show that we are able to faithfully predict
the workload presented to a video server. We also provide
a synthetic trace developed from the model enabling
researchers to also study other problems of interest.}
On the Capacity of a Hybrid Broadcast Multiple Access System for WDM Networks Vinay Vaishampayan, Chao Tian, Mark Feuer
IEEE International Symposium on Information Theory,
2011.
[PDF][BIB]
IEEE Copyright
This version of the work is reprinted here with permission of IEEE for your personal use. Not for redistribution. The definitive version was published in IEEE International Symposium on Information Theory. , 2011-08-01, 10.1109/ISIT.2011.6033967
{Abstract�An information theoretic analysis is presented for
a layered communication system designed for enhancing the
network management capabilities of a wavelength division multiplexed
(WDM) optical network. A theoretical model for the
layered communication system is developed, and is seen to be a
combination of a multiple access and broadcast communication
system. Inner and outer bounds for the capacity region are
derived for both general discrete memoryless model and the
Gaussian model, which provide a complete solution for the
symmetric problem. Comparisons are drawn between the coding
technique suggested by an information theoretic analysis and the
coding method used in a working implementation.}
The definitive version was published in IEEE INFOCOM Cloud Computing Workshop , 2011-04-10
{Cloud computing is a new infrastructure environment
that delivers on the promise of supporting on-demand
services in a flexible manner by scheduling bandwidth, storage
and compute resources on the fly. IPTV services like Video
On Demand (VoD) and Live broadcast TV requires substantial
bandwidth and compute resources to meet the real time requirements
and to handle the very bursty resource requirements
for each of these services. To meet the needs of the bursts of
requests, each with a deadline constraint for both VoD and
LiveTV channel changes, we propose a resource provisioning
framework that allows these services to co-exist on a common
infrastructure by taking advantage of virtualization. We propose
an optimal algorithm that provides the minimum number of
servers needed to fulfill all requests for these services. We prove this
optimality in a general setting for any number of services with
general deadline constraints. By using real world data from an
operational IPTV environment, our results show that anticipating
and thereby enabling the delaying of VoD requests by up to 30
seconds gives significant resource savings even under conservative
environmental assumptions. We also experiment with different
scenarios (by varying the deadline constraints, changing the peak
to average ratios of the constituent services) to compute the
overall savings.}
The definitive version was published in COMSNETS 2011. , 2011-01-05, http://www.comsnets.org/
{Service providers are evolving to provide more video content on-demand. Customers like to watch a variety of entertainment content of their choice and at a time conducive
to their schedules. Catering to this ever-increasing user base requires careful provisioning by the providers to accommodate for both scale and interactivity. In this paper, we examine the usage pattern of several hundreds of thousands of consumers of a nationwide IPTV service, and confirm that viewers are indeed
migrating to what is called �time-shifted� viewing of television programming and movies using digital video recorders or on demand viewing. We also show how users of on-demand content interactively control their viewing experience using �stream control� functions such as fast-forward, rewind, skip, replay, etc. Through careful measurements on an IPTV server, we compute the load due to streaming and handling these stream control events. We then extrapolate from these micro-benchmark
measurement to predict the processing load imposed by users that would resort to using a �network-based� DVR capability if such a service were offered. We use both detailed trace-driven simulations and a simple operational-analysis based model to
predict the capacity requirements of the server complex in the VHO to serve a large population of customers (e.g. a densely populated city like Mumbai). We provide insights on the number of requests serviced by the server, the average time to service
these requests and the response time as perceived by the client.}
The definitive version was published in proceedings of OFC 2011 (Optical Society of America). , Issue paper JWA28, 2011-03-06
{We introduce digital lightpath labeling for DP-QPSK systems, using novel binary encoding to embed a polarization-shift-keyed subchannel. An integrated inline polarimeter powers a compact label receiver with robust tolerance to polarization rotation in a 40Gb/s demonstration. }
{Interactivity is promised by IP-based content distribution, particularly with IPTV. We investigate the user viewing activity for broadcast TV, pre-recorded content using Digital Video Recording (DVR) and video on demand (VoD). Advanced stream control functions (play, pause, skip, rewind, etc.) provide users with a high level of interactivity, but place demands on the distribution infrastructure (servers, network, home-network) that can be difficult to manage at large scale. To support system design as well as network capacity planning, it is necessary to have a good model of user interaction. Using traces from a well-provisioned operational environment with a large user population, we first characterize interactivity for broadcast TV, DVR and VoD. We then develop parametric models of individual users stream control operations for VoD. Our analysis shows that interactive behavior is adequately characterized by two semi-Markov models, one for weekdays and another for weekends. We propose a parametric model for the underlying sojourn time distributions and show that it results in a superior fit compared to well known distributions (generalized Pareto and Weibull). In order to validate that our models faithfully capture user behavior, we compare the workload that a VoD server experiences in response to actual traces and synthetic data generated from our proposed models. }
Rejection of inter-label crosstalk in a digital lightpath labeling system with low-cost, all-wavelength receivers Mark Feuer, Vinay Vaishampayan
2005.
[DOC][BIB]
IEEE Copyright
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Copyright (1992-2009) IEEE. The IEEE owns the copyright to material that is published by the IEEE. Personal use of this material is permitted. However, permission to reprint / republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. Please read the full IEEE copyright policy.
Copyright (1992-2009) IEEE. The IEEE owns the copyright to material that is published by the IEEE. Personal use of this material is permitted. However, permission to reprint / republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. Please read the full IEEE copyright policy.
Copyright (1992-2009) IEEE. The IEEE owns the copyright to material that is published by the IEEE. Personal use of this material is permitted. However, permission to reprint / republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. Please read the full IEEE copyright policy.
Copyright (1992-2009) IEEE. The IEEE owns the copyright to material that is published by the IEEE. Personal use of this material is permitted. However, permission to reprint / republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. Please read the full IEEE copyright policy.
Copyright (1992-2009) IEEE. The IEEE owns the copyright to material that is published by the IEEE. Personal use of this material is permitted. However, permission to reprint / republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. Please read the full IEEE copyright policy.
