Multi-agent distributed adaptive resource allocation (MADARA)
Created by W.Langdon from
gp-bibliography.bib Revision:1.8051
- @Article{Edmondson:2010:IJCNDS,
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author = "James Edmondson and Douglas Schmidt",
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title = "Multi-agent distributed adaptive resource allocation
({MADARA})",
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journal = "International Journal of Communication Networks and
Distributed Systems",
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year = "2010",
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volume = "5",
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number = "3",
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pages = "229--245",
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keywords = "genetic algorithms, genetic programming",
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ISSN = "1754-3924",
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URL = "http://www.inderscience.com/link.php?id=34946",
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URL = "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.150.5912",
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bibsource = "OAI-PMH server at www.inderscience.com",
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language = "eng",
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rights = "Inderscience Copyright",
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abstract = "The component placement problem involves mapping a
component to a particular location and maximising
component utility in grid and cloud systems. It is also
an NP hard resource allocation and deployment problem,
so many common grid and cloud computing libraries, such
as MPICH and Hadoop, do not address this problem, even
though large performance gains can occur by optimising
communications between nodes. This paper provides four
contributions to research on the component placement
problem for grid and cloud computing environments.
First, we present the multi-agent distributed adaptive
resource allocation (MADARA) toolkit, which is designed
to address grid and cloud allocation and deployment
needs. Second, we present a heuristic called the
comparison-based iteration by degree (CID) heuristic,
which we use to approximate optimal deployments in
MADARA. Third, we analyse the performance of applying
the CID heuristic to approximate common grid and cloud
operations, such as broadcast, gather and reduce.
Fourth, we evaluate the results of applying genetic
programming mutation to improve our CID heuristic.",
- }
Genetic Programming entries for
James Edmondson
Douglas C Schmidt
Citations