Abstract
Grid computing environments are distributed systems formed by a heterogeneous and geographically distributed resource set. In spite of the advantages of such paradigm, several problems related to resources availability and resources selection have become a challenge extensively studied by the grid community in last years.
The aim of this work is to provide an intelligent and self-adaptive model for selecting grid resources during applications execution. This adaptive capability is obtained by applying during the selection process an evolutionary method known as Scatter Search (it is based on quality and diversity criteria).
Finally, the model is evaluated in a real grid infrastructure. The results show that the infrastructure throughput is enhanced. Even more, a reduction in the applications execution time and an improvement of the successfully finished tasks rate are also achieved. As a conclusion, the proposed model is a feasible solution for grid applications.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Foster, I.: What is the Grid? A three Point Checklist. GRIDtoday 1(6), 22–25 (2002)
Foster, I.: The Anatomy of the Grid: Enabling Scalable Virtual Organizations. In: Sakellariou, R., Keane, J.A., Gurd, J.R., Freeman, L. (eds.) Euro-Par 2001. LNCS, vol. 2150, pp. 1–4. Springer, Heidelberg (2001)
Laguna, M., Martí, R.: Scatter Search: Methodology and Implementations in C. Kluwer Academic Publishers (2003)
Laguna, M., Martí, R.: Scatter Search. In: Alba, E., Martí, R. (eds.) Metaheuristic Procedures for Training Neural Networks, pp. 139–152. Springer (2006)
Resende, M., Ribeiro, C., Glover, F., Martí, R.: Scatter Search and Path Relinking: Fundamentals, Advances and Applications. In: Gendreau, M., Potvin, J.Y. (eds.) Handbook of Metaheuristics. Springer (2009)
National Network of e-Science, http://www.e-ciencia.es/grid.jsp
National e-Science Grid Portal, http://www.e-ciencia.es/wiki/index.php/Portal:Grid
Huedo, E., Montero, R.S., Llorente, I.M.: A Framework for Adaptive Execution in Grids. Software-Practice & Experience 34(7), 631–651 (2004)
Keung, H.N.L.C., Dyson, J.R.D., Jarvis, S.A., Nudd, G.R.: Self-adaptive and Self-optimising Resource Monitoring for Dynamic Grid Environments. In: Proceedings of the 15th International Workshop on Database and Expert Systems Applications, DEXA 2004, pp. 689-693. IEEE Computer Society (2004)
Vadhiyar, S.S., Dongarra, J.J.: Self Adaptivity in Grid Computing. Concurrency and Computation: Practice & Experience 17(2-4), 235–257 (2005)
Wrzesinska, G., Maasen, J., Bal, H.E.: Self-adaptive Applications on the Grid. In: 12th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, pp. 121–129 (2007)
Groen, D., Harfst, S., Portegies Zwart, S.: On the Origin of Grid Species: The Living Application. In: Allen, G., Nabrzyski, J., Seidel, E., van Albada, G.D., Dongarra, J., Sloot, P.M.A. (eds.) ICCS 2009, Part I. LNCS, vol. 5544, pp. 205–212. Springer, Heidelberg (2009)
Batista, D.M., Da Fonseca, L.S.: A Survey of Self-adaptive Grids. IEEE Communications Magazine 48(7), 94–100 (2010)
Press, W.H., Flannery, B.P., Teukolsky, S.A., Vetterling, W.T.: Numerical Recipies in C. Press Syndicate of the University of Cambridge, New York (1992)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Botón-Fernández, M., Vega-Rodríguez, M.A., Prieto-Castrillo, F. (2013). An Efficient and Self-adaptive Model Based on Scatter Search: Solving the Grid Resources Selection Problem. In: Moreno-Díaz, R., Pichler, F., Quesada-Arencibia, A. (eds) Computer Aided Systems Theory - EUROCAST 2013. EUROCAST 2013. Lecture Notes in Computer Science, vol 8111. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-53856-8_50
Download citation
DOI: https://doi.org/10.1007/978-3-642-53856-8_50
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-53855-1
Online ISBN: 978-3-642-53856-8
eBook Packages: Computer ScienceComputer Science (R0)