150 research outputs found
On Approximating the Sum-Rate for Multiple-Unicasts
We study upper bounds on the sum-rate of multiple-unicasts. We approximate
the Generalized Network Sharing Bound (GNS cut) of the multiple-unicasts
network coding problem with independent sources. Our approximation
algorithm runs in polynomial time and yields an upper bound on the joint source
entropy rate, which is within an factor from the GNS cut. It
further yields a vector-linear network code that achieves joint source entropy
rate within an factor from the GNS cut, but \emph{not} with
independent sources: the code induces a correlation pattern among the sources.
Our second contribution is establishing a separation result for vector-linear
network codes: for any given field there exist networks for which
the optimum sum-rate supported by vector-linear codes over for
independent sources can be multiplicatively separated by a factor of
, for any constant , from the optimum joint entropy
rate supported by a code that allows correlation between sources. Finally, we
establish a similar separation result for the asymmetric optimum vector-linear
sum-rates achieved over two distinct fields and
for independent sources, revealing that the choice of field
can heavily impact the performance of a linear network code.Comment: 10 pages; Shorter version appeared at ISIT (International Symposium
on Information Theory) 2015; some typos correcte
Connectivity and equilibrium in random games
We study how the structure of the interaction graph of a game affects the
existence of pure Nash equilibria. In particular, for a fixed interaction
graph, we are interested in whether there are pure Nash equilibria arising when
random utility tables are assigned to the players. We provide conditions for
the structure of the graph under which equilibria are likely to exist and
complementary conditions which make the existence of equilibria highly
unlikely. Our results have immediate implications for many deterministic graphs
and generalize known results for random games on the complete graph. In
particular, our results imply that the probability that bounded degree graphs
have pure Nash equilibria is exponentially small in the size of the graph and
yield a simple algorithm that finds small nonexistence certificates for a large
family of graphs. Then we show that in any strongly connected graph of n
vertices with expansion the distribution of the number
of equilibria approaches the Poisson distribution with parameter 1,
asymptotically as .Comment: Published in at http://dx.doi.org/10.1214/10-AAP715 the Annals of
Applied Probability (http://www.imstat.org/aap/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Decentralized Erasure Codes for Distributed Networked Storage
We consider the problem of constructing an erasure code for storage over a
network when the data sources are distributed. Specifically, we assume that
there are n storage nodes with limited memory and k<n sources generating the
data. We want a data collector, who can appear anywhere in the network, to
query any k storage nodes and be able to retrieve the data. We introduce
Decentralized Erasure Codes, which are linear codes with a specific randomized
structure inspired by network coding on random bipartite graphs. We show that
decentralized erasure codes are optimally sparse, and lead to reduced
communication, storage and computation cost over random linear coding.Comment: to appear in IEEE Transactions on Information Theory, Special Issue:
Networking and Information Theor
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