Abstract
Small-world property is found in a wide range of natural, biological, social or transport networks. The main idea of this phenomenon is that seemingly distant nodes actually have very short path lengths due to the presence of a small number of shortcut edges running between clusters of nodes. In the present work, we apply this principle for solving the resources selection problem in grid computing environments (distributed systems composed by heterogeneous and geographically dispersed resources). The proposed model expects to find the most efficient resources for a particular grid application in a short number of steps. It also provides a self-adaptive ability for dealing with environmental changes. Finally, this selection model is tested in a real grid infrastructure. From the results obtained it is concluded that both a reduction in execution time and an increase in the successfully completed tasks rate are achieved.
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
Batista, D.M., Da Fonseca, L.S.: A Survey of Self-adaptive Grids. IEEE Communications Magazine 48(7), 94–100 (2010)
Berman, F., Wolski, R., Casanova, H., Cirne, W., Dail, H., Faerman, M., Figueira, S., Hayes, J., Obertelli, G., Schopf, J., Shao, G., Smallen, S., Spring, N., Su, A., Zagorodnov, D.: Adaptive Computing on the Grid Using AppLeS. IEEE Transactions on Parallel and Distributed Systems 14(4), 369–382 (2003)
Du, H., Wu, X., Zhuang, J.: Small-World Optimization Algorithm for Function Optimization. In: Jiao, L., Wang, L., Gao, X.-b., Liu, J., Wu, F. (eds.) ICNC 2006, Part II. LNCS, vol. 4222, pp. 264–273. Springer, Heidelberg (2006)
Erdos, P., Rény, A.: On the Evolution of Random Graphs. Publications of the Mathematical Institute of the Hungarian Academy of Sciences 5, 17–61 (1960)
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)
Foster, I.: What is the Grid? A three Point Checklist. GRIDtoday 1(6), 22–25 (2002)
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: DEXA 2004, Proceedings of the Database and Expert Systems Applications, 15th International Workshop, Washington DC, USA, pp. 689–693 (2004)
Kleinberg, J.: The Small-world Phenomenon: an Algorithm Perspective. In: Proceedings of The Thirty-second Annual ACM Symposium on Theory of Computing, Portland, OR, USA, pp. 163–170 (2000)
Newman, M., Barabási, A.-L., Watts, D.J.: The Structure and Dynamics of Network. Princeton University Press (2006)
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)
Vadhiyar, S.S., Dongarra, J.J.: Self Adaptivity in Grid Computing. Concurrency and Computation: Practice and Experience 17(2-4), 235–257 (2005)
Watts, D.J., Strogatz, S.H.: Collective Dynamics of Small-world Networks. Nature 393, 440–442 (1998)
Wrzesinska, G., Maasen, J., Bal, H.E.: Self-adaptive Applications on the Grid. In: Proceedings of the 12th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, San Jose, California, USA, pp. 121–129 (2007)
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., Castrillo, F.P., Vega-Rodríguez, M.A. (2013). The Small-World Phenomenon Applied to a Self-adaptive Resources Selection Model. In: Esparcia-Alcázar, A.I. (eds) Applications of Evolutionary Computation. EvoApplications 2013. Lecture Notes in Computer Science, vol 7835. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37192-9_9
Download citation
DOI: https://doi.org/10.1007/978-3-642-37192-9_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-37191-2
Online ISBN: 978-3-642-37192-9
eBook Packages: Computer ScienceComputer Science (R0)