Efficient task replication and management for adaptive fault tolerance in Mobile Grid environments

Future Generation Computer Systems

Volumn 23, Issue 2, 2007, Pages 163-178

  Litke, Antonios ^a   Skoutas, Dimitrios ^a   Tserpes, Konstantinos ^a   Varvarigou, Theodora ^a  

^a NATIONAL TECHNICAL UNIVERSITY OF ATHENS   (Greece)

Author keywords

Fault tolerance; Grid computing; Scheduling

Indexed keywords

COMPUTER SIMULATION; DISTRIBUTED COMPUTER SYSTEMS; MIDDLEWARE; MOBILE COMPUTING; RELIABILITY; SCHEDULING;

GRID COMPUTING; MOBILE GRID COMPUTING PARADIGM; RESOURCE MANAGEMENT; WEIBULL RELIABILITY FUNCTION;

FAULT TOLERANT COMPUTER SYSTEMS;

EID: 33748541058     PISSN: 0167739X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.future.2006.04.014     Document Type: Article

References (60)

1. Lyu M.R. Software Fault Tolerance (1995), John Wiley & Sons, Chichester, UK
2. A. Nguyen-Tuong, Integrating fault-tolerance techniques in Grid applications, Ph.D. Dissertation, University of Virginia, August 2000
3. Ramamritham K., Stankovic J.A., and Shiah P.-F. Efficient scheduling algorithms for real-time multiprocessor systems. IEEE Trans. Parallel Distrib. Syst. 1 2 (1990) 184-194
4. Scheduling Working Group of the Grid Forum, Document: 10.5, September 2001
5. Wang F., Ramamritham K., and Stankovic J.A. Determining redundancy levels for fault tolerant real-time systems. IEEE Trans. Comput. 44 February (1995)
6. D. Pisinger, Algorithms for Knapsack problems, Ph.D. Thesis, Dept. of Computer Science, University of Copenhagen, February 1995
7. J.B. Weissman, Fault Tolerant Computing on the Grid: What are My Options? HPDC (1999)
8. Hwang S., and Kesselman C. A flexible framework for fault tolerance in the grid. J. Grid Comput. 1 (2003) 251-272
9. The Globus project, http://www-fp.globus.org/hbm/
10. A. Nguyen-Tuong, A.S. Grimshaw, Using reflection to incorporate fault-tolerance techniques in distributed applications, Computer Science Technical Report, University of Virginia, CS 98-34, 1998
11. Chapin S.J., Katramatos D., Karpovich J., and Grimshaw A. Resource management in Legion. Future Gener. Comput. Syst. 15 5-6 (1999) 583-594
12. Casanova H., Dongarra J., Johnson C., and Miller M. Application-specific tools. In: Foster I., and Kesselman C. (Eds). The GRID: Blueprint for a New Computing Infrastructure (1998) 159-180 (Chapter 7)
13. Plank J.S., Casanova H., Beck M., and Dongarra J.J. Deploying fault tolerance and task migration with NetSolve. Future Gener. Comput. Syst. 15 5 (1999) 745-755
14. Grimshaw A.S., Ferrari A., and West E.A. Mentat. In: Wilson G.V., and Lu P. (Eds). Parallel Programming Using C + + (1996) 382-427 (Chapter 10)
15. Gartner F.C. Fundamentals of fault-tolerant distributed computing in asynchronous environments. ACM Comput. Surv. 31 1 (1999)
16. Chen Q., Ferris M., and Linderoth J.T. FATCOP 2.0: Advanced features in an opportunistic mixed integer programming solver. Ann. Oper. Res. 103 (2001) 17-32
17. Zhuge H., Sun X., Liu J., Yao E., and Chen X. A scalable P2P platform for the knowledge grid. IEEE Trans. Knowl. Data Eng. 17 12 (2005) 1721-1736
18. Q. Lv, P. Cao, E. Cohen, K. Li, S. Shenker, Search and replication in unstructured peer-to-peer networks, in: Proc. 16th Int'l Conf. Supercomputing, June 2002, pp. 84-95
19. Access to Knowledge through the Grid in a Mobile World (AKOGRIMO) Integrated Project FP6-2003-IST-004293, http://www.akogrimo.org/
20. A. Litke, D. Skoutas, T. Varvarigou, Mobile Grid computing: Changes and challenges of resource management in a mobile grid environment, in: Access to Knowledge through the Grid in a Mobile World Workshop, held in conjunction with 5th Int. Conf. on Practical Aspects of Knowledge Management, PAKM 2004, Vienna. Available at http://www.mobilegrids.org/docs/pakm2004/papers/3_Mobile-Grid-Computing.pdf
21. D. Abramson, R. Sosic, J. Giddy, B. Hall, Nimrod: A tool for performing parametised simulations using distributed workstations, in: The 4th IEEE Symposium on High Performance Distributed Computing, Virginia, August 1995
22. Abramson D., Buyya R., and Giddy J. A computational economy for grid computing and its implementation in the Nimrod-G resource broker. Future Gener. Comput. Syst. 18 8 (2002) 1061-1074
23. Berman F., Chien A., Cooper K., Dongarra J., Foster I., Gannon D., Johnsson L., Kennedy K., Kesselman C., Mellor-Crummey J., Reed D., Torczon L., and Wolski R. The GrADS Project: Software support for high-level grid application development. Int. J. High Perform. Comput. Appl. 15 4 (2001) 327-344 Winter
24. Frey J., Tannenbaum T., Foster I., Livny M., and Tuecke S. Condor-G: A computation management agent for multiinstitutional grids. Cluster Comput. 5 (2002) 237-246
25. Faerman M., Figueira S., Hayes J., Obertelli G., Schopf J., Shao G., Smallen S., Spring N., Su A., and Zagorodnov D. Adaptive computing on the grid using AppLeS. IEEE Trans. Parallel Distrib. Syst. 14 4 (2003) 369-382
26. Weng C., and Lu X. Heuristic scheduling for bag-of-tasks applications in combination with QoS in the computational grid. Future Gener. Comput. Syst. 21 (2005) 271-280
27. V. Subramani, R. Kettimuthu, S. Srinivasan, P. Sadayappan, Distributed job scheduling on computational grids using multiple simultaneous requests, in: Proc. of the 11th IEEE International Symposium on High Performance Distributed Computing, Edinburgh, Scotland, July 2002, pp. 359-367
28. The Unicore project, http://www.unicore.org/forum.htm
29. R. Parra-Hernandez, D. Vanderster, N.J. Dimopoulos, Resource management and Knapsack formulations on the grid, in: Proc. of the 5th IEEE/ACM Int. Workshop on Grid Computing, GRID'04
30. Leung J.Y.-T., and Merrill M.L. A note on preemptive, scheduling of periodic, real-time tasks. Inform. Process. Lett. November (1980) 115-118
31. Jackson L.E., and Rouskas G.N. Deterministic preemptive scheduling of real time tasks. IEEE Comput. 35 5 (2002) 72-79
32. A.S. Tanenbaum, M. van Steen, Distributed Systems: Principles and Paradigms, 1st ed., Prenctice Hall, Computer Science
33. Varvarigou T., and Trotter J. Module replication for fault-tolerant real-time distributed systems. IEEE Trans. Reliab. 47 1 (1998) 8-18
34. Reed D.A., Lu C., and Mendes C.L. Reliability challenges in large systems. Future Gener. Comput. Syst. 22 (2006) 293-302
35. D. Nurmi, J. Brevik, R. Wolski, Modeling machine availability in enterprise and wide-area distributed computing environments, UCSB Computer Science Technical Report Number CS2003-28
36. D.C. Montgomery, G.C. Runger, Applied Statistics and Probability for Engineers, 3rd ed. (an Interactive e-text)
37. Meyer P.L. Introductory Probability and Statistical Applications. 2nd ed. (1970), Addison-Wesley (Chapter 11)
38. Scheaffer R.L. Introduction to Probability and Its Applications. 2nd ed. (1995), Duxbury (Section 4.9)
39. R.B. Abernethy, The New Weibull Handbook, 4th ed., ISBN 0-9653062-1-6
40. N. Doulamis, A. Doulamis, A. Panagakis, K. Dolkas, T. Varvarigou, E. Varvarigos, A combined fuzzy-neural network model for non-linear prediction of 3D rendering workload in grid computing, IEEE Trans. Syst. Man Cybern. B. (2004)
41. He X., Sun X.-H., and von Laszewski G. QoS guided min-min heuristic for grid task scheduling. Grid Computing. J. Comput. Sci. Technol. 18 4 (2003) (special issue)
42. Carrington L., Snavely A., and Wolter N. A performance prediction framework for scientific applications. Future Gener. Comput. Syst. 22 (2006) 336-346
43. Wolski R., Spring N., and Hayes J. The network weather service: A distributed resource performance forecasting service for metacomputing. Future Gener. Comput. Syst. 15 (1999) 757-768
44. Gong L., Sun X.H., and Waston E. Performance modeling and prediction of non-dedicated network computing. IEEE Trans. Comput. 51 9 (2002)
45. Gao Y., Rong H., and Huang J.Z. Adaptive grid job scheduling with genetic algorithms. Future Gener. Comput. Syst. 21 (2005) 151-161
46. A. Litke, K. Tserpes, T. Varvarigou, Computational workload prediction for Grid oriented industrial applications: The case of 3D-image rendering, in: Proceedings of Cluster Computing and Grid, CCGrid2005, vol. 2, 2005, pp. 962-969
47. D. Pisinger, Algorithms for knapsack problems, Ph.D. Thesis, Dept. of Computer Science, University of Copenhagen, February 1995
48. Litke A., Tserpes K., Dolkas K., and Varvarigou T. A task replication and fair resource management scheme for fault tolerant grids. Advances in Grid Computing-EGC 2005. Lecture Notes in Computer Science vol. 3470 (2005) 1022-1031
49. Martello S., Pisinger D., and Toth P. New trends in exact algorithms for the 0-1 knapsack problem. Eur. J. Oper. Res. 123 (2000) 325-332
50. Martello S., and Toth P. Knapsack Problems: Algorithms and Computer Implementations (1990), John Wiley & Sons
51. D. Ghosh, Heuristics for knapsack problems: Comparative survey and sensitivity analysis, Fellowship Dissertation, IIM Calcutta, India, 1997
52. G. Ghosh, B. Goldengorin, The binary knapsack problem: Solutions with guaranteed quality, Research Report 01A64, University of Groningen, 2001
53. Chu P.C., and Beasley J.E. A genetic algorithm for the multidimensional knapsack problem. J. Heuristics 4 1 (1998) 63-86
54. Cotta C., and Troya J.M. A hybrid genetic algorithm for the 0-1 multiple knapsack problem. In: Smith G.D., Steele N.C., and Albrecht R.F. (Eds). Artificial Neural Nets and Genetic Algorithms 3 (1998), Springer-Verlag 251-255
55. A.B. Simões, E. Costa, An evolutionary approach to the zero/one Knapsack problem: Testing ideas from biology, in: Proc. of the Fifth Int. Conf. on Neural Networks and Genetic Algorithms, ICANNGA'01, Prague, April 2001, pp. 236-239
56. Sahni S. Data Structures, Algorithms, and Applications in Java. 2nd ed. (2004), Silicon Press
57. Preiss B.R. Data Structures and Algorithms with Object-Oriented Design Patterns in C + + (1999), John Wiley & Sons
58. The Open Grid Services Architecture, Version 1.0, http://www.ggf.org/documents/GWD-I-E/GFD-I.030.pdf
59. OASIS Web Services Resource Framework (WSRF), http://www.oasis-open.org
60. Simple Object Access Protocol, http://www.w3.org/TR/soap/