143 research outputs found
Balanced Allocations: A Simple Proof for the Heavily Loaded Case
We provide a relatively simple proof that the expected gap between the
maximum load and the average load in the two choice process is bounded by
, irrespective of the number of balls thrown. The theorem
was first proven by Berenbrink et al. Their proof uses heavy machinery from
Markov-Chain theory and some of the calculations are done using computers. In
this manuscript we provide a significantly simpler proof that is not aided by
computers and is self contained. The simplification comes at a cost of weaker
bounds on the low order terms and a weaker tail bound for the probability of
deviating from the expectation
Dynamic Traitor Tracing for Arbitrary Alphabets: Divide and Conquer
We give a generic divide-and-conquer approach for constructing
collusion-resistant probabilistic dynamic traitor tracing schemes with larger
alphabets from schemes with smaller alphabets. This construction offers a
linear tradeoff between the alphabet size and the codelength. In particular, we
show that applying our results to the binary dynamic Tardos scheme of Laarhoven
et al. leads to schemes that are shorter by a factor equal to half the alphabet
size. Asymptotically, these codelengths correspond, up to a constant factor, to
the fingerprinting capacity for static probabilistic schemes. This gives a
hierarchy of probabilistic dynamic traitor tracing schemes, and bridges the gap
between the low bandwidth, high codelength scheme of Laarhoven et al. and the
high bandwidth, low codelength scheme of Fiat and Tassa.Comment: 6 pages, 1 figur
The Probability to Hit Every Bin with a Linear Number of Balls
Assume that balls are thrown independently and uniformly at random into
bins. We consider the unlikely event that every bin receives at least
one ball, showing that where . Note
that, due to correlations, is not simply the probability that any single
bin receives at least one ball. More generally, we consider the event that
throwing balls into bins results in at least balls in each
bin
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
Self-Stabilizing Repeated Balls-into-Bins
We study the following synchronous process that we call "repeated
balls-into-bins". The process is started by assigning balls to bins in
an arbitrary way. In every subsequent round, from each non-empty bin one ball
is chosen according to some fixed strategy (random, FIFO, etc), and re-assigned
to one of the bins uniformly at random.
We define a configuration "legitimate" if its maximum load is
. We prove that, starting from any configuration, the
process will converge to a legitimate configuration in linear time and then it
will only take on legitimate configurations over a period of length bounded by
any polynomial in , with high probability (w.h.p.). This implies that the
process is self-stabilizing and that every ball traverses all bins in
rounds, w.h.p
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