223 research outputs found
Network Codes for Real-Time Applications
We consider the scenario of broadcasting for real-time applications and loss
recovery via instantly decodable network coding. Past work focused on
minimizing the completion delay, which is not the right objective for real-time
applications that have strict deadlines. In this work, we are interested in
finding a code that is instantly decodable by the maximum number of users.
First, we prove that this problem is NP-Hard in the general case. Then we
consider the practical probabilistic scenario, where users have i.i.d. loss
probability and the number of packets is linear or polynomial in the number of
users. In this scenario, we provide a polynomial-time (in the number of users)
algorithm that finds the optimal coded packet. The proposed algorithm is
evaluated using both simulation and real network traces of a real-time Android
application. Both results show that the proposed coding scheme significantly
outperforms the state-of-the-art baselines: an optimal repetition code and a
COPE-like greedy scheme.Comment: ToN 2013 Submission Versio
Delivery Time Reduction for Order-Constrained Applications using Binary Network Codes
Consider a radio access network wherein a base-station is required to deliver
a set of order-constrained messages to a set of users over independent erasure
channels. This paper studies the delivery time reduction problem using
instantly decodable network coding (IDNC). Motivated by time-critical and
order-constrained applications, the delivery time is defined, at each
transmission, as the number of undelivered messages. The delivery time
minimization problem being computationally intractable, most of the existing
literature on IDNC propose sub-optimal online solutions. This paper suggests a
novel method for solving the problem by introducing the delivery delay as a
measure of distance to optimality. An expression characterizing the delivery
time using the delivery delay is derived, allowing the approximation of the
delivery time minimization problem by an optimization problem involving the
delivery delay. The problem is, then, formulated as a maximum weight clique
selection problem over the IDNC graph wherein the weight of each vertex
reflects its corresponding user and message's delay. Simulation results suggest
that the proposed solution achieves lower delivery and completion times as
compared to the best-known heuristics for delivery time reduction
Rate Aware Instantly Decodable Network Codes
This paper addresses the problem of reducing the delivery time of data
messages to cellular users using instantly decodable network coding (IDNC) with
physical-layer rate awareness. While most of the existing literature on IDNC
does not consider any physical layer complications and abstract the model as
equally slotted time for all users, this paper proposes a cross-layer scheme
that incorporates the different channel rates of the various users in the
decision process of both the transmitted message combinations and the rates
with which they are transmitted. The consideration of asymmetric rates for
receivers reflects more practical application scenarios and introduces a new
trade-off between the choice of coding combinations for various receivers and
the broadcasting rate for achieving shorter completion time. The completion
time minimization problem in such scenario is first shown to be intractable.
The problem is, thus, approximated by reducing, at each transmission, the
increase of an anticipated version of the completion time. The paper solves the
problem by formulating it as a maximum weight clique problem over a newly
designed rate aware IDNC (RA-IDNC) graph. The highest weight clique in the
created graph being potentially not unique, the paper further suggests a
multi-layer version of the proposed solution to improve the obtained results
from the employed completion time approximation. Simulation results indicate
that the cross-layer design largely outperforms the uncoded transmissions
strategies and the classical IDNC scheme
On Minimizing the Maximum Broadcast Decoding Delay for Instantly Decodable Network Coding
In this paper, we consider the problem of minimizing the maximum broadcast
decoding delay experienced by all the receivers of generalized instantly
decodable network coding (IDNC). Unlike the sum decoding delay, the maximum
decoding delay as a definition of delay for IDNC allows a more equitable
distribution of the delays between the different receivers and thus a better
Quality of Service (QoS). In order to solve this problem, we first derive the
expressions for the probability distributions of maximum decoding delay
increments. Given these expressions, we formulate the problem as a maximum
weight clique problem in the IDNC graph. Although this problem is known to be
NP-hard, we design a greedy algorithm to perform effective packet selection.
Through extensive simulations, we compare the sum decoding delay and the max
decoding delay experienced when applying the policies to minimize the sum
decoding delay [1] and our policy to reduce the max decoding delay. Simulations
results show that our policy gives a good agreement among all the delay aspects
in all situations and outperforms the sum decoding delay policy to effectively
minimize the sum decoding delay when the channel conditions become harsher.
They also show that our definition of delay significantly improve the number of
served receivers when they are subject to strict delay constraints
Completion Time Reduction in Instantly Decodable Network Coding Through Decoding Delay Control
For several years, the completion time and decoding delay problems in
Instantly Decodable Network Coding (IDNC) were considered separately and were
thought to completely act against each other. Recently, some works aimed to
balance the effects of these two important IDNC metrics but none of them
studied a further optimization of one by controlling the other. In this paper,
we study the effect of controlling the decoding delay to reduce the completion
time below its currently best known solution. We first derive the
decoding-delay-dependent expressions of the users' and overall completion
times. Although using such expressions to find the optimal overall completion
time is NP-hard, we design a novel heuristic that minimizes the probability of
increasing the maximum of these decoding-delay-dependent completion time
expressions after each transmission through a layered control of their decoding
delays. Simulation results show that this new algorithm achieves both a lower
mean completion time and mean decoding delay compared to the best known
heuristic for completion time reduction. The gap in performance becomes
significant for harsh erasure scenarios
A Graph Model for Opportunistic Network Coding
Recent advancements in graph-based analysis and solutions of instantly
decodable network coding (IDNC) trigger the interest to extend them to more
complicated opportunistic network coding (ONC) scenarios, with limited increase
in complexity. In this paper, we design a simple IDNC-like graph model for a
specific subclass of ONC, by introducing a more generalized definition of its
vertices and the notion of vertex aggregation in order to represent the storage
of non-instantly-decodable packets in ONC. Based on this representation, we
determine the set of pairwise vertex adjacency conditions that can populate
this graph with edges so as to guarantee decodability or aggregation for the
vertices of each clique in this graph. We then develop the algorithmic
procedures that can be applied on the designed graph model to optimize any
performance metric for this ONC subclass. A case study on reducing the
completion time shows that the proposed framework improves on the performance
of IDNC and gets very close to the optimal performance
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