143,792 research outputs found
Coordination-Free Byzantine Replication with Minimal Communication Costs
State-of-the-art fault-tolerant and federated data management systems rely on fully-replicated designs in which all participants have equivalent roles. Consequently, these systems have only limited scalability and are ill-suited for high-performance data management. As an alternative, we propose a hierarchical design in which a Byzantine cluster manages data, while an arbitrary number of learners can reliable learn these updates and use the corresponding data.
To realize our design, we propose the delayed-replication algorithm, an efficient solution to the Byzantine learner problem that is central to our design. The delayed-replication algorithm is coordination-free, scalable, and has minimal communication cost for all participants involved. In doing so, the delayed-broadcast algorithm opens the door to new high-performance fault-tolerant and federated data management systems. To illustrate this, we show that the delayed-replication algorithm is not only useful to support specialized learners, but can also be used to reduce the overall communication cost of permissioned blockchains and to improve their storage scalability
A Distributed Economics-based Infrastructure for Utility Computing
Existing attempts at utility computing revolve around two approaches. The
first consists of proprietary solutions involving renting time on dedicated
utility computing machines. The second requires the use of heavy, monolithic
applications that are difficult to deploy, maintain, and use.
We propose a distributed, community-oriented approach to utility computing.
Our approach provides an infrastructure built on Web Services in which modular
components are combined to create a seemingly simple, yet powerful system. The
community-oriented nature generates an economic environment which results in
fair transactions between consumers and providers of computing cycles while
simultaneously encouraging improvements in the infrastructure of the
computational grid itself.Comment: 8 pages, 1 figur
Work Alienation among IT Workers: A Cross-Cultural Gender Comparison
Information Technology (IT) has experienced a worrisome decline in female participation over two decades, much of which can be attributed to fewer women choosing IT careers. However, women IT professionals also demonstrate mid-career turnover for reasons such as work-life balance, work exhaustion, role ambiguity, role conflict, and growth needs. This study explores alienation among women IT professionals and examines factors that lead to work alienation and abandonment of IT careers. Such alienation appears to be less prevalent in Asian countries where women perceive IT careers to be more conducive to female participation. A comparison among women from American and Asian cultures is proposed
Distributed simulation of city inundation by coupled surface and subsurface porous flow for urban flood decision support system
We present a decision support system for flood early warning and disaster
management. It includes the models for data-driven meteorological predictions,
for simulation of atmospheric pressure, wind, long sea waves and seiches; a
module for optimization of flood barrier gates operation; models for stability
assessment of levees and embankments, for simulation of city inundation
dynamics and citizens evacuation scenarios. The novelty of this paper is a
coupled distributed simulation of surface and subsurface flows that can predict
inundation of low-lying inland zones far from the submerged waterfront areas,
as observed in St. Petersburg city during the floods. All the models are
wrapped as software services in the CLAVIRE platform for urgent computing,
which provides workflow management and resource orchestration.Comment: Pre-print submitted to the 2013 International Conference on
Computational Scienc
Towards Loosely-Coupled Programming on Petascale Systems
We have extended the Falkon lightweight task execution framework to make
loosely coupled programming on petascale systems a practical and useful
programming model. This work studies and measures the performance factors
involved in applying this approach to enable the use of petascale systems by a
broader user community, and with greater ease. Our work enables the execution
of highly parallel computations composed of loosely coupled serial jobs with no
modifications to the respective applications. This approach allows a new-and
potentially far larger-class of applications to leverage petascale systems,
such as the IBM Blue Gene/P supercomputer. We present the challenges of I/O
performance encountered in making this model practical, and show results using
both microbenchmarks and real applications from two domains: economic energy
modeling and molecular dynamics. Our benchmarks show that we can scale up to
160K processor-cores with high efficiency, and can achieve sustained execution
rates of thousands of tasks per second.Comment: IEEE/ACM International Conference for High Performance Computing,
Networking, Storage and Analysis (SuperComputing/SC) 200
Bots as Virtual Confederates: Design and Ethics
The use of bots as virtual confederates in online field experiments holds
extreme promise as a new methodological tool in computational social science.
However, this potential tool comes with inherent ethical challenges. Informed
consent can be difficult to obtain in many cases, and the use of confederates
necessarily implies the use of deception. In this work we outline a design
space for bots as virtual confederates, and we propose a set of guidelines for
meeting the status quo for ethical experimentation. We draw upon examples from
prior work in the CSCW community and the broader social science literature for
illustration. While a handful of prior researchers have used bots in online
experimentation, our work is meant to inspire future work in this area and
raise awareness of the associated ethical issues.Comment: Forthcoming in CSCW 201
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