243,991 research outputs found
Parallel Sort-Based Matching for Data Distribution Management on Shared-Memory Multiprocessors
In this paper we consider the problem of identifying intersections between
two sets of d-dimensional axis-parallel rectangles. This is a common problem
that arises in many agent-based simulation studies, and is of central
importance in the context of High Level Architecture (HLA), where it is at the
core of the Data Distribution Management (DDM) service. Several realizations of
the DDM service have been proposed; however, many of them are either
inefficient or inherently sequential. These are serious limitations since
multicore processors are now ubiquitous, and DDM algorithms -- being
CPU-intensive -- could benefit from additional computing power. We propose a
parallel version of the Sort-Based Matching algorithm for shared-memory
multiprocessors. Sort-Based Matching is one of the most efficient serial
algorithms for the DDM problem, but is quite difficult to parallelize due to
data dependencies. We describe the algorithm and compute its asymptotic running
time; we complete the analysis by assessing its performance and scalability
through extensive experiments on two commodity multicore systems based on a
dual socket Intel Xeon processor, and a single socket Intel Core i7 processor.Comment: Proceedings of the 21-th ACM/IEEE International Symposium on
Distributed Simulation and Real Time Applications (DS-RT 2017). Best Paper
Award @DS-RT 201
Efficient asynchronous accumulators for distributed PKI
Cryptographic accumulators are a tool for compact set representation and secure set membership proofs. When an element is added to a set by means of an accumulator, a membership witness is generated. This witness can later be used to prove the membership of the element. Typically, the membership witness has to be synchronized with the accumulator value, and to be updated every time another element is added to the accumulator. In this work we propose an accumulator that, unlike any prior scheme, does not require strict synchronization.
In our construction a membership witness needs to be updated only a logarithmic number of times in the number of subsequent element additions. Thus, an out-of-date witness can be easily made current. Vice versa, a verifier with an out-of-date accumulator value can still verify a current membership witness. These properties make our accumulator construction uniquely suited for use in distributed applications, such as blockchain-based public key infrastructures
Statistical-mechanical iterative algorithms on complex networks
The Ising models have been applied for various problems on information
sciences, social sciences, and so on. In many cases, solving these problems
corresponds to minimizing the Bethe free energy. To minimize the Bethe free
energy, a statistical-mechanical iterative algorithm is often used. We study
the statistical-mechanical iterative algorithm on complex networks. To
investigate effects of heterogeneous structures on the iterative algorithm, we
introduce an iterative algorithm based on information of heterogeneity of
complex networks, in which higher-degree nodes are likely to be updated more
frequently than lower-degree ones. Numerical experiments clarified that the
usage of the information of heterogeneity affects the algorithm in BA networks,
but does not influence that in ER networks. It is revealed that information of
the whole system propagates rapidly through such high-degree nodes in the case
of Barab{\'a}si-Albert's scale-free networks.Comment: 7 pages, 6 figure
Semi-Streaming Algorithms for Annotated Graph Streams
Considerable effort has been devoted to the development of streaming
algorithms for analyzing massive graphs. Unfortunately, many results have been
negative, establishing that a wide variety of problems require
space to solve. One of the few bright spots has been the development of
semi-streaming algorithms for a handful of graph problems -- these algorithms
use space .
In the annotated data streaming model of Chakrabarti et al., a
computationally limited client wants to compute some property of a massive
input, but lacks the resources to store even a small fraction of the input, and
hence cannot perform the desired computation locally. The client therefore
accesses a powerful but untrusted service provider, who not only performs the
requested computation, but also proves that the answer is correct.
We put forth the notion of semi-streaming algorithms for annotated graph
streams (semi-streaming annotation schemes for short). These are protocols in
which both the client's space usage and the length of the proof are . We give evidence that semi-streaming annotation schemes
represent a substantially more robust solution concept than does the standard
semi-streaming model. On the positive side, we give semi-streaming annotation
schemes for two dynamic graph problems that are intractable in the standard
model: (exactly) counting triangles, and (exactly) computing maximum matchings.
The former scheme answers a question of Cormode. On the negative side, we
identify for the first time two natural graph problems (connectivity and
bipartiteness in a certain edge update model) that can be solved in the
standard semi-streaming model, but cannot be solved by annotation schemes of
"sub-semi-streaming" cost. That is, these problems are just as hard in the
annotations model as they are in the standard model.Comment: This update includes some additional discussion of the results
proven. The result on counting triangles was previously included in an ECCC
technical report by Chakrabarti et al. available at
http://eccc.hpi-web.de/report/2013/180/. That report has been superseded by
this manuscript, and the CCC 2015 paper "Verifiable Stream Computation and
Arthur-Merlin Communication" by Chakrabarti et a
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