Title :
Distributed Evolutionary Algorithms in Heterogeneous Environments
Author :
Salto, Carolina ; Luna, F. ; Alba, Enrique
Author_Institution :
Fac. de Ing., Univ. Nac. de La Pampa Argentine, Argentina
Abstract :
Distributed computing environments are usually composed of many heterogeneous computers able to work cooperatively. We analyze the impact in the performance of a parallel metaheuristic when it is executed using a set of heterogeneous computing resources. Following a well-defined methodology, the aim of the paper is to use all the computing resources but at the same time to be efficient in time. Our conclusion is that both the solution quality and the numeric effort are comparable to that achieved by using a (faster) homogeneous platform, the traditional environment to execute this kind of algorithms.
Keywords :
genetic algorithms; parallel algorithms; performance evaluation; distributed computing environments; distributed evolutionary algorithms; distributed genetic algorithm; heterogeneous computers; heterogeneous computing resource; parallel metaheuristic; performance impact analysis; Benchmark testing; Clocks; Hardware; Program processors; Sociology; Statistics;
Conference_Titel :
P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC), 2013 Eighth International Conference on
Conference_Location :
Compiegne
DOI :
10.1109/3PGCIC.2013.105