Abstract
Evolutionary Algorithms (EA) are well suited for solving optimisation problems, especially NP-complete problems. This paper presents the application of the Evolutionary Algorithm GLEAM (General Learning and Evolutionary Algorithm and Method) in the field of grid computing. Here, grid resources like computing power, software, or storage have to be allocated to jobs that are running in heterogeneous computing environments. The problem is similar to industrial resource scheduling, but has additional characteristics like co-scheduling and high dynamics within the resource pool and the set of requesting jobs. The paper describes the deployment of GLEAM in the global optimising grid resource broker GORBA (Global Optimising Resource Broker and Allocator) and the first promising results in a grid simulation environment.
An erratum to this chapter can be found at http://dx.doi.org/10.1007/11914952_55.
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References
Nissen, V.: Quadratic Assignment. In: Bäck, T., Fogel, D., Michalewicz, Z. (eds.) Handbook of Evolutionary Computation, Oxford University Press, New York (1997) (sect. G9.10)
Hoheisel, A., Der, U.: Dynamic Workflows for Grid Applications. In: Cracow Grid Workshop (2003)
Hovestadt, M., Kao, O., Keller, A., Streit, A.: Scheduling in HPC Resource Management Systems: Queuing vs. Planning. In: Feitelson, D.G., Rudolph, L., Schwiegelshohn, U. (eds.) JSSPP 2003. LNCS, vol. 2862, pp. 1–20. Springer, Heidelberg (2003)
Blume, C.: GLEAM - A System for Simulated “Intuitive Learning”. In: Schwefel, H.-P., Männer, R. (eds.) PPSN 1990. LNCS, vol. 496, pp. 48–54. Springer, Heidelberg (1991)
Blume, C., Jakob, W.: GLEAM – An Evolutionary Algorithm for Planning and Control Based on Evolution Strategy. In: Conf. Proc. GECCO 2002 (2002) (Late Breaking Papers)
Rechenberg, I.: Evolutionsstrategie 1994. Frommann-Holzboog Verlag, Stuttgart - Bad Cannstatt (in German) (1994)
Michalewicz, Z.: Genetic Algorithms + Data Structures = Evolution Programs. Springer, Berlin (1992)
Jakob, W., Quinte, A., Stucky, K.-U., Süß, W.: Optimised Scheduling of Grid Resources Using Hybrid Evolutionary Algorithms. In: Wyrzykowski, R., Dongarra, J., Meyer, N., Waśniewski, J. (eds.) PPAM 2005. LNCS, vol. 3911, pp. 406–413. Springer, Heidelberg (2006)
Karp, R.M.: Reducibility Among Combinatorial Problems. In: Complexity of Computer Computations, Sympos. Proc., pp. 85–103. Plenum Press, New York (1972)
Ali, A., Anjum, A., Mehmood, A., McClatchey, R., Willers, I., Bunn, J., Newman, H., Thomas, M., Steenberg, C.: A Taxonomy and Survey of Grid Resource Planning and Reservation Systems for Enabled Analysis Environment. In: Proceedings of the 2004 International Symposium on Distributed Computing and Applications to Business, Engineering and Science, DCABES 2004, Wuhan Hubei, P.R. China, September 13th-16th (2004)
Krauter, K., Buyya, R., Maheswaran, M.: A Taxonomy and Survey of Grid Resource Management Systems for Distributed Computing. International Journal of Software: Practice and Experience (SPE) 32(2), 135–164 (2002)
Buyya, R., Murshed, M., Abramson, D., Venugopal, S.: Scheduling Parameter Sweep Applications on Global Grids: A Deadline and Budget Constrained Cost-Time Optimisation Algorithm. Softw. Pract. Exper. 35, 491–512 (2005)
Sample, N., Keyani, P., Wiederhold, G.: Scheduling under uncertainty: Planning for the ubiquitous grid. In: Arbab, F., Talcott, C. (eds.) COORDINATION 2002. LNCS, vol. 2315, p. 300. Springer, Heidelberg (2002)
Nabrzyski, J., Schopf, J.M., Weglarz, J. (eds.): Grid Resource Management – State of the Art and Future Trends. Kluwer Academic Publishers, Dordrecht (2004)
YarKhan, A., Dongarra, J.: Experiments with Scheduling Using Simulated Annealing in a Grid Environment. In: Parashar, M. (ed.) GRID 2002. LNCS, vol. 2536, pp. 232–242. Springer, Heidelberg (2002)
Glover, F., Laguna, M.: Tabu Search. Kluwer Academic Publishers, Dordrecht (1997)
Abraham, A., Buyya, R., Nath, B.: Nature’s Heuristics for Scheduling Jobs on Computational Grids. In: Int. Conf. on Advanced Computing and Communications (2000)
Aggarwal, M., Kent, R.D., Ngom, A.: Genetic algorithm based scheduler for computational grids. In: IEEE Conference Proceedings (High Performance Computing Systems and Applications, 2005. HPCS 2005), vol. 15-18, pp. 209–215 (2005)
Gao, Y., Rong, H.Q., Huang, J.Z.: Adaptive grid job scheduling with genetic algorithms. Future Generation Computer Systems 21, 151–161 (2005)
Song, S., Kwok, Y.-K., Hwang, K.: Security-Driven Heuristics and A Fast Genetic Algorithm for Trusted Grid Job Scheduling. In: 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS 2005) – Papers, p. 65a (2005)
Di Martino, V., Mililotti, M.: Sub optimal scheduling in a grid using genetic algorithms. Parallel Computing 30, 553–565 (2004)
Schmitz, F., Schneider, O., Karlsruhe, F.: The CampusGrid Test Bed at Forschungszentrum Karlsruhe. In: Sloot, P.M.A., Hoekstra, A.G., Priol, T., Reinefeld, A., Bubak, M. (eds.) EGC 2005. LNCS, vol. 3470, pp. 1139–1142. Springer, Heidelberg (2005)
Blume, C., Gerbe, M.: Deutliche Senkung der Produktionskosten durch Optimierung des Ressourceneinsatzes. Automatisierungstechnische Praxis (atp) 36, Oldenbourg, München, 25-29 (1994) (in German)
Jakob, W., Quinte, A., et al.: Opt. of a Micro Fluidic Component Using a Parallel EA and Simulation Based on Discrete Element Methods. In: Hernandez, S., et al. (eds.) Computer Aided Design of Structures VII, Proc. of OPTI 2001, pp. 337–346. WIT Press, Southampton (2001)
Jakob, W.: HyGLEAM - An Approach to Generally Applicable Hybridization of Evolutionary Algorithms. In: Guervós, J.J.M., Adamidis, P.A., Beyer, H.-G., Fernández-Villacañas, J.-L., Schwefel, H.-P. (eds.) PPSN 2002. LNCS, vol. 2439, pp. 527–536. Springer, Heidelberg (2002)
Süß, W., Jakob, W., Quinte, A., Stucky, K.-U.: GORBA: Resource Brokering in Grid Environments using Evolutionary Algorithms. In: Proc. 17th IASTED Intern. Conference on Parallel and Distributed Computing Systems (PDCS), Phoenix, AZ, November 14-16, pp. S19–S24 (2005)
Hoheisel, A., Der, U.: An XML-Based Framework for Loosely Coupled Applications on Grid Environments. In: Sloot, P.M.A., Abramson, D., Bogdanov, A.V., Gorbachev, Y.E., Dongarra, J., Zomaya, A.Y., et al. (eds.) ICCS 2003. LNCS, vol. 2657, pp. 245–254. Springer, Heidelberg (2003)
Tchernykh, A., Ramírez, J.M., Avetisyan, A.I., Kuzjurin, N.N., Grushin, D., Zhuk, S.: Two Level Job-Scheduling Strategies for a Computational Grid. In: Wyrzykowski, R., Dongarra, J., Meyer, N., Waśniewski, J. (eds.) PPAM 2005. LNCS, vol. 3911, pp. 774–781. Springer, Heidelberg (2006)
Tobita, T., Kasahara, H.: A standard task graph set for fair evaluation of multiprocessor scheduling algorithms. Journal of Scheduling 5, 379–394 (2002)
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Stucky, KU., Jakob, W., Quinte, A., Süß, W. (2006). Solving Scheduling Problems in Grid Resource Management Using an Evolutionary Algorithm. In: Meersman, R., Tari, Z. (eds) On the Move to Meaningful Internet Systems 2006: CoopIS, DOA, GADA, and ODBASE. OTM 2006. Lecture Notes in Computer Science, vol 4276. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11914952_14
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DOI: https://doi.org/10.1007/11914952_14
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