Search
Abstract
Artificial intelligence techniques are capable to handle a large amount of information collected over the web. In this paper, big data paradigm has been studied in volunteer and grid system called Comcute that is optimized by a genetic programming scheduler. This scheduler can optimize load balancing and resource cost. Genetic programming optimizer has been applied for finding the Pareto solu-tions. Finally, some results from numerical experiments have been shown.
Citations
-
1 1
CrossRef
-
0
Web of Science
-
1 0
Scopus
Authors (4)
Cite as
Full text
full text is not available in portal
Keywords
Details
- Category:
- Conference activity
- Type:
- materiały konferencyjne indeksowane w Web of Science
- Published in:
-
LECTURE NOTES IN COMPUTER SCIENCE
no. 1,
edition Artificial Intelligence and Soft Computing,
pages 771 - 782,
ISSN: 0302-9743 - Title of issue:
- Artificial Intelligence and Soft Computing. - Part I strony 771 - 782
- Language:
- English
- Publication year:
- 2014
- Bibliographic description:
- Balicki J., Korłub W., Szymański J., Zakidalski M..: Big Data Paradigm Developed in Volunteer Grid System with Genetic Programming Scheduler, W: Artificial Intelligence and Soft Computing. - Part I, 2014, SPRINGER-VERLAG BERLIN,.
- DOI:
- Digital Object Identifier (open in new tab) 10.1007/978-3-319-07173-2_66
- Verified by:
- Gdańsk University of Technology
seen 129 times