Dynamic job scheduling on the grid environment using the great deluge algorithm

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4671 LNCS, Issue , 2007, Pages 283-292

  McMullan, Paul ^a   McCollum, Barry ^a  

^a QUEEN'S UNIVERSITY BELFAST   (United Kingdom)

Author keywords

Great deluge; Grid; Job scheduling; Network; Parallel processing; Simulated annealing

Indexed keywords

COMPUTATIONAL METHODS; JOB ANALYSIS; PARALLEL ALGORITHMS; SIMULATED ANNEALING;

COMPUTATIONAL GRID PROCESSOR NETWORK; SCHEDULING PROCESSES;

PARALLEL PROCESSING SYSTEMS;

EID: 38149137342     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-73940-1_29     Document Type: Conference Paper

References (18)

1. Fernandez-Baca, D.: Allocating Modules to Processors in a Distributed System. IEEE Transactions on Software Engineering 15(11), 1427-1436 (1989)
2. Tracy, D., et al.: A Comparison of eleven Static Heuristics for Mapping a Class of Independent Tasks onto Heterogeneous Distributed Computing Systems. Journal of Parallel and Distributed Computing 61, 810-837 (2001)
3. Liu, L., Zhan, J., Lian, L.: A Runtime Scheduling Approach with Respect to Job Parallelism for Computational Grid. In: Proc. Of 3rd International Conference of Grid and Cooperative Computing (2004)
4. Mika, M., et al.: A Metaheuristic Approach to Scheduling Workflow Jobs on a Grid. In: Grid Resource Management: State of the Art and Future Trends, Kluwer Academic Publishers, Boston (2003)
5. Dueck, G.: Threshold Accepting: A General Purpose Optimization Algorithm Appearing Superior to Simulated Annealing. J. Computational Physics 90, 161-175 (1990)
6. Kirkpatrick, S., Gellat, J.C.D., Vecci, M.P.: Optimization by Simulated Annealing. Science 220, 671-680 (1983)
7. 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)
8. Fidanova, S.: Simulated Annealing for Grid Scheduling Problem. In: IEEE John Vincent Atanasoft International Symposium on Modern Computing (JVA '06), pp. 41-45 (2006)
9. McMullan, P.: An Extended Implementation of the Great Deluge Algorithm for Course Timetabling. In: International Conference on Computational Science (ICCS 2007). LNCS, Springer, Heidelberg (to appear)
10. Kendall, G., Mohamad, M.: Channel Assignment in Cellular Communication Using a Great Deluge Hyper-Heuristic. In: Proc. of IEEE International Conference on Network (ICON'04), pp. 769-773 (2004)
11. Petrovic, S., Burke, E.K.: University Timetabling, Handbook of Scheduling: Algorithms, Models and Performance Analysis, ch. 45. CRC Press, Boca Raton (2004)
12. McMullan, P., Roche, T.: An Intelligent Space Allocation and Planning Tool for Educational Requirements. Technical Report, RTS-TR-2005-2 (2005)
13. Berman, F., et al.: The GrADS Project: Software Support for high-level Grid application development. Int. Journal of High Performance Computing Applications 15(4), 327-344 (2001)
14. Foster, I., Kesselman, C.: The Globus Toolkit. In: Foster, I., Kesselmanm, C. (eds.) The Grid: Blueprint for a New Computing Infrastructure, ch. 11, Morgan Kaufmann, San Francisco (1999)
15. Wolski, R., Spring, N., Hayes, J.: The Network Weather Service: a Distributed Resource Performance Forecasting System for Metacomputing. Future Generation Computing Systems 15(5-6), 757-768 (1999)
16. Burke, E.K., Newall, J.P.: Solving Examination Timetabling Problems through Adaptation of Heuristic Orderings, Technical Report, Nottingham (2002)
17. Abramson, D., Krishnamoorthy, M., Dang, H.: Simulated Annealing Cooling Schedules for the School Timetabling Problem. Asia-Pacific Journal of Operation Research 16, 1-22 (1999)
18. Marler, R.T., Arora, J.S.: Survey of multi-objective optimization methods for engineering. Journal Structural and Multidisciplinary Optimization 26(6), 369-395 (2004)