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Optimizing Cloud Resources for Delivering IPTV Services through Virtualization
Vaneet Aggarwal, Vijay Gopalakrishnan, Rittwik Jana, Kadangode Ramakrishnan, Vinay Vaishampayan
Special Issue of IEEE Transactions on Multimedia: Cloud-Based Mobile Media: Infrastructure, Services,
2013.
[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 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.}
Beyond Interference Avoidance: Distributed Sub-network Scheduling in Wireless Networks with Local Views
Vaneet Aggarwal, Pedro Santacruz, Ashutosh Sabharwal
IEEE Infocomm 2013,
2013.
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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 2012 , 2013-04-14
{In most wireless networks, nodes have only limited
local information about the network state, which includes
connectivity and channel state information. With limited local
information about the network, each node’s knowledge is mismatched,
therefore they must make distributed decisions. In
this paper, we pose the following question - if every node has
network state information only about a small neighborhood, how
and when should nodes choose to transmit? While scheduling
answers the above question for point-to-point physical layers
which are designed for an interference-avoidance paradigm, we
look for answers in cases when interference can be embraced by
advanced code design, as suggested by results in network information
theory. To make progress on this challenging problem, we
propose a distributed algorithm which achieves rates higher than
interference-avoidance based link scheduling, especially if each
node knows more than one hop of network state information.}
Writing on Insertion Paper
Vaneet Aggarwal
IEEE ICC,
2012.
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[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 ICC. , 2012-06-10
{ The capacity of insertion channels, even in the presence of feedback, is an open problem in information theory. In this paper, we prove that the capacity of insertion channel with non-causal insertion information at the transmitter is $1$ even when the receiver do not know the insertion pattern. This paper considers two insertion models, namely random insertion model and the sticky insertion model. For both these models, interference-free capacity of $1$ is obtained even when the receiver does not know the interference (insertion pattern).}
Optimizing Cloud Resources for Delivering IPTV Services through Virtualization
Vaneet Aggarwal, Rittwik Jana, Vijay Gopalakrishnan, Kadangode Ramakrishnan, Vinay Vaishampayan
FOURTH INTERNATIONAL CONFERENCE ON COMMUNICATION SYSTEMS AND NETWORKS (COMSNETS),
2012.
[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 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.}
Grassmannian Packing Based Aligned Precoder Designs for Interference Channels
Vaneet Aggarwal, Vinay Vaishampayan, Xiaodong Wang, Khawla Al Najjar
Conference on Information Sciences and Systems,
2012.
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[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 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.}
Full- or Half-Duplex? A Capacity Analysis with Bounded Radio Resources
Vaneet Aggarwal, N Shankaranarayanan, Melissa Duarte, Ashutosh Sabharwal
IEEE ITW 2012,
2012.
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[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 2012. , 2012-09-03
{Full duplex communication requires nodes to cancel their own interference. Recent
work have proved the feasibility of full duplex communications using software radios.
In this paper, we address capacity comparisons when the total amount of analog radio hardware is bounded. Under this constraint, it is not immediately clear if one should use these radios to perform full-duplex self-interference cancelation or use the radios to give additional MIMO multiplexing advantage. We find that repurposing radios for cancellation, instead of using all of them for half-duplex over-the-air transmission, can be
beneficial since the resulting full-duplex system performs better in some practical SNR regimes and almost always outperforms half duplex in symmetric degrees-of-freedom (large SNR regime).}
Datacenter Net Profit Optimization with Deadline Dependent Pricing
Wei Pang, Peng Zhang, Tian Lan, Vaneet Aggarwal
IEEE CISS,
2012.
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[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 2012 , Volume $vol, 2012-03-22
{This paper considers deadline dependent pricing
and its impact to datacenter net profit optimization.We formulate
the problem by jointly maximizing total revenue as a function of
individual job deadlines and minimizing electricity cost through
job scheduling over different time and locations. These two
complementary objectives�the maximization of revenue and
the minimization of cost�are mutually-dependent due to the
coupling of job completion time and scheduling decisions. Leveraging
a new approximation method for job completion time,
we develop two low-complexity, distributed algorithms for the
net profit optimization. Through numerical evaluations, we show
the efficacy of the proposed algorithms as well as the net profit
improvements.}
The Effect of Eavesdroppers on Network Connectivity: A Secrecy Graph Approach
Vaneet Aggarwal, Satashu Goel, Robert Calderbank, Aylin Yener
IEEE Transactions on Information Forensics and Security,
2011.
[BIB]
{This paper investigates the effect of eavesdroppers on network connectivity, using a wiretap model and
percolation theory. The wiretap model captures the effect of eavesdroppers on link security. A link exists
between two nodes only if the secrecy capacity of that link is positive. Network connectivity is defined in
percolation sense, i.e., connectivity exists if an infinite connected component exists in the corresponding
secrecy graph. We consider uncertainty in location of eavesdroppers, which is modeled directly at the
network level as correlated failures in the secrecy graph. Our approach attempts to bridge the gap between
physical layer security under uncertain channel state information and network level connectivity under
secrecy constraints. For square and triangular lattice secrecy graphs, we obtain bounds on the percolation
threshold, which is the critical value of the probability of occurrence of an eavesdropper, above which
network connectivity does not exist. For Poisson secrecy graphs, degree distribution and mean value of
upper and lower bounds on node degree are obtained. Further, inner and outer bounds on the achievable
region for network connectivity are obtained. Both analytic and simulation results show that uncertainty
in location of eavesdroppers has a dramatic effect on network connectivity in a secrecy graph.}
Scalable Geocasting for Vehicular Communications
Rajesh Panta, Rittwik Jana, Robert Hall, Josh Auzins, Vaneet Aggarwal
IEEE Vehicular Networking Conference, 2011,
2011.
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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 Vehicular Networking Conference, 2011. , 2011-11-14
{This paper presents GeoVCom, a robust geocast
protocol for vehicular networks. GeoVCom allows a vehicle to
send geocast messages to all vehicles in a given geographical area
without the sender having any knowledge about which vehicles
are present in that area. GeoVCom is ad hoc, scalable and can
handle communications under a wide variability of traffic load.
We investigate the performance of GeoVCom in both simulation
and real world tests using an implementation running on smart
phones. Our field deployment and simulation results show that
the number of transmissions per geocast message is kept low,
significantly outperforming conventional flooding algorithms and
at the same time maintaining a high (over 90%) success rate.}
On Achieving Local View Capacity Via Maximal Independent Graph Scheduling
Vaneet Aggarwal, Salman Avestimehr, Ashutosh Sabharwal
IEEE Trans. Inf. Theory,
2011.
[BIB]
IEEE Copyright
test
{�If we know more, we can achieve more.� This adage
also applies to networks, where more information about the
network state translates into higher sum-rates. In this paper, we
formalize this increase of sum-rate with increased knowledge of
the network state. The knowledge of network state is measured in
terms of the number of hops of information available to each node
and is labeled each node�s local view. To understand how much
capacity is lost due to limited information, we propose to use
the metric of normalized sum-capacity, which is the h-hop local
view sum-capacity divided by global-view sum-capacity. For the
cases of one and two-local view, we characterize the normalized
sum-capacity for many classes of deterministic and Gaussian
interference networks. In many cases, a scheduling scheme called
maximal independent graph scheduling is shown to achieve
normalized sum-capacity. We also show that its generalization
for one-hop local view, labeled coded set scheduling, achieves
capacity whenever its uncoded counterpart fails to do so.}
Maximal k-Clique Scheduling: A simple algorithm to bound maximal independent graph scheduling
Vaneet Aggarwal, Salman Avestimehr, Ashutosh Sabharwal, Kanes Sutuntivorakoon
Annual Allerton Conference on Communication, Control, and Computing,
2011.
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[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 Annual Allerton Conference on Communication, Control, and Computing , 2011-09-30
{In this paper, we study interference networks with
local views, where each node only knows the channel gains of
h hops around them, leading to mismatched knowledge about
the network. For networks with a local view, we propose a
new sub-network scheduling called Maximal k-Clique Scheduling
(MCS). A key benefit of MCS is that it can be explicitly
constructed and hence easier to analyze compared to prior subgraph
schedulers. Our main result is that MCS can be used to
bound the performance from above and below of a more complex
sub-graph scheduling algorithm, known as Maximal Independent
Graph Scheduling (MIGS), which in many cases does not have
a known explicit construction.}
Exploiting Virtualization for Delivering Cloud-based IPTV Services
Vaneet Aggarwal, Xu Chen, Vijay Gopalakrishnan, Rittwik Jana, Kadangode Ramakrishnan, Vinay Vaishampayan
IEEE INFOCOM Workshop on Cloud Computing ,
2011.
[PDF]
[BIB]
IEEE Copyright
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.}
Characterizing Fairness for 3G Wireless Networks
Vaneet Aggarwal, Rittwik Jana, Kadangode Ramakrishnan, Jeffrey Pang, N Shankaranarayanan
IEEE LANMAN 2011,
2011.
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[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 LANMAN 2011. , 2011-10-13
{The end to end system data performance over a 3G cellular network depends on many factors such as the number of users, interference, multipath propagation, radio resource management techniques as well as the interaction between these mechanisms and the transport protocol's flow and congestion mechanisms. Using controlled experiments in a public cell site, we investigate the interaction between TCP and the 3G UMTS/HSPA network's resource allocation, and its effect on fairness in the throughput achieved across multiple (up to 26) TCP flows in a loaded cell sector. Our field measurement results indicate that TCP fairness fluctuates significantly when the air interface (radio link) is the bottleneck. We also observe that TCP fairness is substantially better when the backhaul link (a fixed wired link) is the bottleneck, instead of the air interface. We speculate that the fairness of TCP flows is adversely impacted by the mismatch between the resource allocation mechanisms of TCP's flow and congestion control and that of the Radio Access Network (RAN).}
Bits About the Channel: Multi-round Protocols for Two-way Fading Channels
Vaneet Aggarwal, Ashutosh Sabharwal
IEEE Transactions on Information Theory,
2011.
[BIB]
{Most communication systems use some form of feedback, often related to channel state information. In this paper, we study diversity multiplexing tradeoff for both FDD and TDD systems, when both receiver and transmitter knowledge about the channel is noisy and potentially mismatched.
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For FDD systems, we first extend the achievable tradeoff region for 1.5 rounds of message passing to get higher diversity compared to the best known scheme, in the regime of higher multiplexing gains. We then break the mold of all current channel state based protocols by using multiple rounds of conferencing to extract more bits about the actual channel. This iterative refinement of the channel increases the diversity order with every round of communication. The protocols are on-demand in nature, using high powers for training and feedback only when the channel is in poor states. The key result is that the diversity multiplexing tradeoff with perfect training and $K$ levels of perfect feedback can be achieved, even when there are errors in training the receiver and errors in the feedback link, with a multi-round protocol which has $K$ rounds of training and $K-1$ rounds of binary feedback. The above result can be viewed as a generalization of Zheng and Tse, and Aggarwal and Sabharwal, where the result was shown to hold for $K=1$ and $K=2$ respectively.
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For TDD systems, we also develop new achievable strategies with multiple rounds of communication between the transmitter and the receiver, which use the reciprocity of the forward and the feedback channel. The multi-round TDD protocol achieves a diversity-multiplexing tradeoff which uniformly dominates its FDD counterparts, where no channel reciprocity is available.}
