Abstract
Grids are very dynamic and their workload is impossible to predict. As a result systems using them need to offer mechanisms for adapting to the new configurations. To address this issue many scheduling policies have been created. In a Grid environment in which tasks needing to be scheduled arrive constantly it is costly to lend some computing resources to only one request consisting of jobs and postpone all others as long as the current one is executing. As a result a scheduling algorithm which minimizes each task’s estimated execution time by considering the total waiting time of a task, the relocation to a faster resource once a threshold has been reached and the fact that it should not be physically relocated at each reassignment should be considered. This paper tries to offer a solution based on the above. To validate the model a comparison with other scheduling algorithms is performed.
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
Casanova, H., et al.: Heuristics for Scheduling Parameter Sweep Applications in Grid Environments. In: The 9th Heterogeneous Computing Workshop (HCW 2000), pp. 349–363. IEEE Press, Los Alamitos (2000)
Chiang, S., Arpaci-Dusseau, A.C., Vernon, M.K.: The Impact of More Accurate Requested Runtimes on Production Job Scheduling Performance. In: Feitelson, D.G., Rudolph, L., Schwiegelshohn, U. (eds.) JSSPP 2002. LNCS, vol. 2537, pp. 103–127. Springer, Heidelberg (2002)
Dong, F., Akl, S.G.: Scheduling algorithms for grid computing: State of the art and open problems. Technical report, Queen’s University (2006)
Feo, T.A., Resende, M.G.C.: Greedy Randomized Adaptive Search Procedures. Journal of Global Optimization 6, 109–133 (1995)
Fujimoto, N., Hagihara, K.: A comparison among grid scheduling algorithms for independent coarse-grained tasks. In: International Symposium on Applications and the Internet Workshops, pp. 674–680. IEEE Press, Los Alamitos (2004)
Gao, Y., Rong, H., Huang, J.: Adaptive grid job scheduling with genetic algorithms. Future Gener. Comput. Syst. 21, 151–161 (2005)
Kurowski, K., et al.: Improving Grid Level Throughput Using Job Migration And Rescheduling. Scientific Programming 12(4), 263–273 (2004)
Lee, C., Schartzman, Y., Hardy, J., Snavely, A.: Are User Runtime Estimates Inherently Inaccurate? In: Feitelson, D.G., Rudolph, L., Schwiegelshohn, U. (eds.) JSSPP 2004. LNCS, vol. 3277, pp. 253–263. Springer, Heidelberg (2005)
Maheswaran, M., et al.: Dynamic Matching and Scheduling of a Class of Independent Tasks onto Heterogeneous Computing Systems. In: The 8th Heterogeneous Computing Workshop (HCW 1999), pp. 30–44. IEEE Press, Los Alamitos (1999)
Mu’alem, A.W., Feitelson, D.G.: Utilization, Predictability, Workloads, and User Runtime Estimates in Scheduling the IBM SP2 with Backfilling. IEEE Transactions in Parallel Distributed Systems 12(6), 529–543 (2001)
Sakellariou, R., Zhao, H.: A Low-Cost Rescheduling Policy for Efficient Mapping of Workflows on Grid Systems. Scientific Programming 12(4), 253–262 (2004)
Smith, W., Foster, I.T., Taylor, V.E.: Predicting Application Run Times Using Historical Information. In: Feitelson, D.G., Rudolph, L. (eds.) IPPS-WS 1998, SPDP-WS 1998, and JSSPP 1998. LNCS, vol. 1459, pp. 122–142. Springer, Heidelberg (1998)
Srinivasan, S., Kettimuthu, R., Subramani, V., Sadayappan, P.: Characterization of Backfilling Strategies for Parallel Job Scheduling. In: Proceedings of the 2002 International Conference on Parallel Processing Workshops, pp. 514–519. IEEE Press, Los Alamitos (2002)
Suter, F., Casanova, H.: Extracting Synthetic Multi-Cluster Platform Configurations from Grid 5000 for Driving Simulation Experiments, Tech. Rep. RT-0341, INRIA (2007)
YarKhan, A., Dongarra, J.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)
Zhao, H., Sakellariou, R.: An Experimental Investigation Into the Rank Function of the Heterogeneous Earliest Finish Time Scheduling Algorithm. In: Kosch, H., Böszörményi, L., Hellwagner, H. (eds.) Euro-Par 2003. LNCS, vol. 2790, pp. 189–194. Springer, Heidelberg (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Frîncu, M.E. (2009). Dynamic Scheduling Algorithm for Heterogeneous Environments with Regular Task Input from Multiple Requests. In: Abdennadher, N., Petcu, D. (eds) Advances in Grid and Pervasive Computing. GPC 2009. Lecture Notes in Computer Science, vol 5529. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01671-4_19
Download citation
DOI: https://doi.org/10.1007/978-3-642-01671-4_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-01670-7
Online ISBN: 978-3-642-01671-4
eBook Packages: Computer ScienceComputer Science (R0)