63,865 research outputs found
The Minrank of Random Graphs
The minrank of a graph is the minimum rank of a matrix that can be
obtained from the adjacency matrix of by switching some ones to zeros
(i.e., deleting edges) and then setting all diagonal entries to one. This
quantity is closely related to the fundamental information-theoretic problems
of (linear) index coding (Bar-Yossef et al., FOCS'06), network coding and
distributed storage, and to Valiant's approach for proving superlinear circuit
lower bounds (Valiant, Boolean Function Complexity '92).
We prove tight bounds on the minrank of random Erd\H{o}s-R\'enyi graphs
for all regimes of . In particular, for any constant ,
we show that with high probability,
where is chosen from . This bound gives a near quadratic
improvement over the previous best lower bound of (Haviv and
Langberg, ISIT'12), and partially settles an open problem raised by Lubetzky
and Stav (FOCS '07). Our lower bound matches the well-known upper bound
obtained by the "clique covering" solution, and settles the linear index coding
problem for random graphs.
Finally, our result suggests a new avenue of attack, via derandomization, on
Valiant's approach for proving superlinear lower bounds for logarithmic-depth
semilinear circuits
Alignment based Network Coding for Two-Unicast-Z Networks
In this paper, we study the wireline two-unicast-Z communication network over
directed acyclic graphs. The two-unicast-Z network is a two-unicast network
where the destination intending to decode the second message has apriori side
information of the first message. We make three contributions in this paper:
1. We describe a new linear network coding algorithm for two-unicast-Z
networks over directed acyclic graphs. Our approach includes the idea of
interference alignment as one of its key ingredients. For graphs of a bounded
degree, our algorithm has linear complexity in terms of the number of vertices,
and polynomial complexity in terms of the number of edges.
2. We prove that our algorithm achieves the rate-pair (1, 1) whenever it is
feasible in the network. Our proof serves as an alternative, albeit restricted
to two-unicast-Z networks over directed acyclic graphs, to an earlier result of
Wang et al. which studied necessary and sufficient conditions for feasibility
of the rate pair (1, 1) in two-unicast networks.
3. We provide a new proof of the classical max-flow min-cut theorem for
directed acyclic graphs.Comment: The paper is an extended version of our earlier paper at ITW 201
A class of index coding problems with rate 1/3
An index coding problem with messages has symmetric rate if all
messages can be conveyed at rate . In a recent work, a class of index coding
problems for which symmetric rate is achievable was characterised
using special properties of the side-information available at the receivers. In
this paper, we show a larger class of index coding problems (which includes the
previous class of problems) for which symmetric rate is
achievable. In the process, we also obtain a stricter necessary condition for
rate feasibility than what is known in literature.Comment: Shorter version submitted to ISIT 201
Local Graph Coloring and Index Coding
We present a novel upper bound for the optimal index coding rate. Our bound
uses a graph theoretic quantity called the local chromatic number. We show how
a good local coloring can be used to create a good index code. The local
coloring is used as an alignment guide to assign index coding vectors from a
general position MDS code. We further show that a natural LP relaxation yields
an even stronger index code. Our bounds provably outperform the state of the
art on index coding but at most by a constant factor.Comment: 14 Pages, 3 Figures; A conference version submitted to ISIT 2013;
typos correcte
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
"Graph Entropy, Network Coding and Guessing games"
We introduce the (private) entropy of a directed graph (in a new network coding sense) as well as a number of related concepts. We show that the entropy of a directed graph is identical to its guessing number and can be bounded from below with the number of vertices minus the size of the graph’s shortest index code. We show that the Network Coding solvability of each specific multiple unicast network is completely determined by the entropy (as well as by the shortest index code) of the directed graph that occur by identifying each source node with each corresponding target node. Shannon’s information inequalities can be used to calculate up- per bounds on a graph’s entropy as well as calculating the size of the minimal index code. Recently, a number of new families of so-called non-shannon-type information inequalities have been discovered. It has been shown that there exist communication networks with a ca- pacity strictly ess than required for solvability, but where this fact cannot be derived using Shannon’s classical information inequalities. Based on this result we show that there exist graphs with an entropy that cannot be calculated using only Shannon’s classical information inequalities, and show that better estimate can be obtained by use of certain non-shannon-type information inequalities
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