28,967 research outputs found
Graphs, Matrices, and the GraphBLAS: Seven Good Reasons
The analysis of graphs has become increasingly important to a wide range of
applications. Graph analysis presents a number of unique challenges in the
areas of (1) software complexity, (2) data complexity, (3) security, (4)
mathematical complexity, (5) theoretical analysis, (6) serial performance, and
(7) parallel performance. Implementing graph algorithms using matrix-based
approaches provides a number of promising solutions to these challenges. The
GraphBLAS standard (istc- bigdata.org/GraphBlas) is being developed to bring
the potential of matrix based graph algorithms to the broadest possible
audience. The GraphBLAS mathematically defines a core set of matrix-based graph
operations that can be used to implement a wide class of graph algorithms in a
wide range of programming environments. This paper provides an introduction to
the GraphBLAS and describes how the GraphBLAS can be used to address many of
the challenges associated with analysis of graphs.Comment: 10 pages; International Conference on Computational Science workshop
on the Applications of Matrix Computational Methods in the Analysis of Modern
Dat
Sustainable Development Report: Blockchain, the Web3 & the SDGs
This is an output paper of the applied research that was conducted between July 2018 - October 2019 funded by the Austrian Development Agency (ADA) and conducted by the Research Institute for Cryptoeconomics at the Vienna University of Economics and Business and RCE Vienna (Regional Centre of Expertise on Education for Sustainable Development).Series: Working Paper Series / Institute for Cryptoeconomics / Interdisciplinary Researc
Sustainable Development Report: Blockchain, the Web3 & the SDGs
This is an output paper of the applied research that was conducted between July 2018 - October 2019 funded by the Austrian Development Agency (ADA) and conducted by the Research Institute for Cryptoeconomics at the Vienna University of Economics and Business and RCE Vienna (Regional Centre of Expertise on Education for Sustainable Development).Series: Working Paper Series / Institute for Cryptoeconomics / Interdisciplinary Researc
Contrasting Views of Complexity and Their Implications For Network-Centric Infrastructures
There exists a widely recognized need to better understand
and manage complex âsystems of systems,â ranging from
biology, ecology, and medicine to network-centric technologies.
This is motivating the search for universal laws of highly evolved
systems and driving demand for new mathematics and methods
that are consistent, integrative, and predictive. However, the theoretical
frameworks available today are not merely fragmented
but sometimes contradictory and incompatible. We argue that
complexity arises in highly evolved biological and technological
systems primarily to provide mechanisms to create robustness.
However, this complexity itself can be a source of new fragility,
leading to ârobust yet fragileâ tradeoffs in system design. We
focus on the role of robustness and architecture in networked
infrastructures, and we highlight recent advances in the theory
of distributed control driven by network technologies. This view
of complexity in highly organized technological and biological systems
is fundamentally different from the dominant perspective in
the mainstream sciences, which downplays function, constraints,
and tradeoffs, and tends to minimize the role of organization and
design
Tiny Groups Tackle Byzantine Adversaries
A popular technique for tolerating malicious faults in open distributed
systems is to establish small groups of participants, each of which has a
non-faulty majority. These groups are used as building blocks to design
attack-resistant algorithms.
Despite over a decade of active research, current constructions require group
sizes of , where is the number of participants in the system.
This group size is important since communication and state costs scale
polynomially with this parameter. Given the stubbornness of this logarithmic
barrier, a natural question is whether better bounds are possible.
Here, we consider an attacker that controls a constant fraction of the total
computational resources in the system. By leveraging proof-of-work (PoW), we
demonstrate how to reduce the group size exponentially to while
maintaining strong security guarantees. This reduction in group size yields a
significant improvement in communication and state costs.Comment: This work is supported by the National Science Foundation grant CCF
1613772 and a C Spire Research Gif
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