Cloud-based Evolutionary Parallel Computation Using Low Cost Storage Services

Author

Arenas, M.G. ; Merelo, J.J. ; Castillo, P. ; Romero, G. ; Laredo, JLJ ; Mora, A.

Author_Institution

Sch. of Comput. Sci. & Telecomunications, Univ. of Granada, Granada, Spain

fYear

2011

fDate

21-23 Nov. 2011

Firstpage

56

Lastpage

61

Abstract

In this paper we will check several different, and difficult, problems, and present what effects the automatic load-balancing and asynchrony have on the speed of resolution of problems. We conclude that the effects of parallelization are noted with difficult problems, although there is a complicated interplay between the number of nodes and migration rate that makes difficult to say exactly what is the best combination of them. This paper uses Drop box as free storage service to connect several heterogeous computers to run an evolutionary algorithm. The algorithmic performance of the system has been proved in previous papers.

Keywords

cloud computing; evolutionary computation; algorithmic performance; asynchrony; automatic load-balancing; cloud-based evolutionary parallel computation; drop box; evolutionary algorithm; free storage service; heterogeous computer; low cost storage services; migration rate; Cloud computing; Computational modeling; Computers; Delay; Evolutionary computation; Synchronization; cloud computing; dropbox;

fLanguage

English

Publisher

ieee

Conference_Titel

Network Cloud Computing and Applications (NCCA), 2011 First International Symposium on

Conference_Location

Toulouse

Print_ISBN

978-1-4577-1667-6

Type

conf

DOI

10.1109/NCCA.2011.16

Filename

6123438