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Grid resource management: state of the art and future trends
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TLDR
An introduction to Grid applications and technologies is provided and the important role that resource management will play in future developments is discussed.Abstract:
The emergence and widespread adoption of Grid computing has been fueled by continued growth in both our understanding of application requirements and the sophistication of the technologies used to meet these requirements. We provide an introduction to Grid applications and technologies and discuss the important role that resource management will play in future developments.read more
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An introduction to mathematical statistical and its applications / Richard J. Larsen, Morris L. Marx
Richard J. Larsen,Morris L. Marx +1 more
TL;DR: In this article, Monte Carlo techniques are used to estimate the probability of a given set of variables for a particular set of classes of data, such as conditional probability and hypergeometric probability.
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A game-theoretic method of fair resource allocation for cloud computing services
TL;DR: A QoS constrained resource allocation problem is considered, in which service demanders intend to solve sophisticated parallel computing problem by requesting the usage of resources across a cloud-based network, and a cost of each computational service depends on the amount of computation.
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A taxonomy of Data Grids for distributed data sharing, management, and processing
TL;DR: In this article, the key concepts behind Data Grids and compare them with other data sharing and distribution paradigms such as content delivery networks, peer-to-peer networks, and distributed databases.
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Scheduling of scientific workflows in the ASKALON grid environment
TL;DR: This paper evaluates three algorithms namely genetic, HEFT, and simple "myopic" and compares incremental workflow partitioning against the full-graph scheduling strategy and demonstrates that full- graph scheduling with the HEFT algorithm performs best.
References
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Basic Local Alignment Search Tool
TL;DR: A new approach to rapid sequence comparison, basic local alignment search tool (BLAST), directly approximates alignments that optimize a measure of local similarity, the maximal segment pair (MSP) score.
Book
Genetic algorithms in search, optimization, and machine learning
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
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Optimization by Simulated Annealing
TL;DR: There is a deep and useful connection between statistical mechanics and multivariate or combinatorial optimization (finding the minimum of a given function depending on many parameters), and a detailed analogy with annealing in solids provides a framework for optimization of very large and complex systems.
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Equation of state calculations by fast computing machines
TL;DR: In this article, a modified Monte Carlo integration over configuration space is used to investigate the properties of a two-dimensional rigid-sphere system with a set of interacting individual molecules, and the results are compared to free volume equations of state and a four-term virial coefficient expansion.
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Emergence of Scaling in Random Networks
TL;DR: A model based on these two ingredients reproduces the observed stationary scale-free distributions, which indicates that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.