Výsledky vyhledávání - "Wouter Minnebo"

On a class of push and pull strategies with single migrations and limited probe rate

Autor: Wouter Minnebo, Benny Van Houdt, Tim Hellemans

Publikováno v: Performance evaluation

In this paper we introduce a general class of rate-based push and pull load balancing strategies, assuming there is no central dispatcher and nodes rely on probe messages for communication. Under a pull strategy lightly loaded nodes send random probe

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4ba480bbeb7f7e56c935f0980b541622
https://hdl.handle.net/10067/1450820151162165141

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Analysis of rate-based pull and push strategies with limited migration rates in large distributed networks

Autor: Benny Van Houdt, Wouter Minnebo

Publikováno v: 9th EAI International Conference on Performance Evaluation Methodologies and Tools, December 1416, 2015, Berlin, Germany

In this paper we analyze the performance of pull and push strategies in large homogeneous distributed systems where the number of job transfers per time unit is limited. Job transfer strategies which rely on lightly-loaded servers to attract jobs fro

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fe408529a5fb7f00c0a487b573cdb9cc
https://hdl.handle.net/10067/1304730151162165141

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Improved rate-based pull and push strategies in large distributed networks

Autor: Wouter Minnebo, Benny Van Houdt

Publikováno v: MASCOTS 2013 : IEEE 21st International Symposium on Modeling, Analysis & Simulation of Computer and Telecommunication Systems (MASCOTS), 2013, San Francisco, Calif., USA
MASCOTS

Large distributed systems benefit from the ability to exchange jobs between nodes to share the overall workload. To exchange jobs, nodes rely on probe messages that are either generated by lightly-loaded or highly-loaded nodes, which corresponds to a

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::14ff0725f51ddea51ddd5dc4f1d84043
https://hdl.handle.net/10067/1149240151162165141

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Separating the wheat from the chaff: on feature selection and feature importance in regression random forests and symbolic regression

Autor: Wouter Minnebo, Sean Stijven, Katya Vladislavleva

Publikováno v: Proceedings of the 13th Annual Conference Companion on Genetic and Evolutionary Computation (GECCO'11), July 12-16, Dublin, Ireland
GECCO (Companion)

Feature selection in high-dimensional data sets is an open problem with no universal satisfactory method available. In this paper we discuss the requirements for such a method with respect to the various aspects of feature importance and explore them

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::02e6844f1b1df09f5d944d9b1a32b47b
https://hdl.handle.net/10067/1247910151162165141

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