Artificial Neural Network support to monitoring of the evolutionary driven security aware scheduling in computational distributed environments

Future Generation Computer Systems

Volumn 51, Issue , 2015, Pages 72-86

  Grzonka, Daniel ^a   Kołodziej, Joanna ^a   Tao, Jie ^b   Khan, Samee Ullah ^c  

^a CRACOW UNIVERSITY OF TECHNOLOGY   (Poland)

^b KARLSRUHE INSTITUTE OF TECHNOLOGY   (Germany)

^c NORTH DAKOTA STATE UNIVERSITY   (United States)

Author keywords

Artificial Neural Network; Computational grids; Distributed environments; Genetic based schedulers; Monitoring; Security awareness

Indexed keywords

DISTRIBUTED COMPUTER SYSTEMS; MOBILE SECURITY; MONITORING; NEURAL NETWORKS; SCHEDULING; SCHEDULING ALGORITHMS;

COMPUTATIONAL GRIDS; DISTRIBUTED COMPUTING ENVIRONMENT; DISTRIBUTED ENVIRONMENTS; GENETIC POPULATION; GENETIC-BASED SCHEDULERS; SCHEDULING PROBLEM; SECURITY AWARENESS; SERVICE FUNCTIONALITIES;

GRID COMPUTING;

EID: 84930576215     PISSN: 0167739X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.future.2014.10.031     Document Type: Article

References (42)

1. F. Pop, C. Dobre, V. Cristea, Genetic algorithm for DAG scheduling in grid environments, in: Proc. of 2009 IEEE 5th International Conference on Intelligent Computer Communication and Processing, 2009, pp. 299-305.
2. A. Shelestov, S. Skakun, and O. Kussul Intelligent model of user behavior in distributed systems Int. J. Inf. Theor. Appl. 15 2008 70 75
3. D. Chen, D. Li, M. Xiong, H. Bao, and X. Li GPGPU-aided ensemble empirical-mode decomposition for EEG analysis during anesthesia IEEE Trans. Inf. Technol. Biomed. 14 6 2010 1417 1427
4. W. Peng, J. Tao, L. Wang, H. Marten, D. Chen, Towards providing cloud functionalities for grid users, in: Proc. of 2011 IEEE 17th International Conference on Parallel and Distributed Systems, ICPADS, 2011, pp. 965-970.
5. S. Song, K. Hwang, and Y.-K. Kwok Risk-resilient heuristics and genetic algorithms for security- assured grid job scheduling IEEE Trans. Comput. 55 6 2006 703 719
6. S. Song, K. Hwang, and Y.K. Kwok Trusted grid computing with security binding and trust integration J. Grid Comput. 2005
7. J. Kołodziej, and F. Xhafa Meeting security and user behaviour requirements in grid scheduling Simul. Modell. Pract. Theory 19 1 2011 213 226 10.1016/j.simpat.2010.06.007
8. J. Kołodziej, and F. Xhafa A game-theoretic and hybrid genetic meta-heuristic model for security-assured scheduling of independent jobs in computational grids Proc. of CISIS 2010 2010 IEEE Press USA 93 100
9. H. Pucha, Y.C. Hu, and Z.M. Mao On the impact of research network based testbeds on wide-area experiments Proc. of the 6th ACM SIGCOMM Conference on Internet Measurement 2006 2006 ACM 133 146
10. S. Ali, H.J. Siegel, M. Maheswaran, D. Hensgen, Task execution time modeling for heterogeneous computing systems, in: Proceedings of Heterogeneous Computing Workshop, 2000, pp. 185-199.
11. F. Xhafa, L. Barolli, and A. Durresi Batch mode schedulers for grid systems Int. J. Web Grid Serv. 3 1 2007 19 37
12. D. Grzonka, J. Kołodziej, J. Tao, Using artificial neural network for monitoring and supporting the grid scheduler performance, in: Proc. of 28th European Conference on Modelling and Simulation, Brescia, Italy, 2014, pp. 515-522.
13. S. Hotovy, Workload evolution on the Cornell Theory Center IBM SP2, in: Job Scheduling Strategies for Parallel, Proc. Workshop, IPPS'96, 1996, pp. 27-40.
14. S. Haykin Neural Networks: A Comprehensive Foundation second ed. 1999 Prentice-Hall Englewood Cliffs, NJ
15. H.E. Aguirre, and K. Tanaka Working principles, behavior, and performance of MOEAs on MNK-landscapes European J. Oper. Res. 181 2007 1670 1690
16. A. Abraham, R. Buyya, B. Nath, Nature's heuristics for scheduling jobs on computational grids, in: Proc. of the 8th IEEE ACC, India, 2000.
17. M. Bartschi Wall A genetic algorithm for resource-constrained scheduling (Ph.D. Thesis) 1996 Massachusetts Institute of Technology MA
18. S.K. Garg, R. Buyya, and H.J. Segel Scheduling parallel aplications on utility grids: time and cost trade-off management B. Mans, Proc. of the 32nd ACSC, Wellington, New Zealand CRPIT vol. 91 2009 ACS 139 147 Ed.
19. J. Kołodziej, and F. Xhafa Enhancing the genetic-based scheduling in computational Grids by a structured hierarchical population Future Gener. Comput. Syst. 27 2011 1035 1046 10.1016/j.future.2011.04.011
20. Z. Michalewicz Genetic Algorithms + Data Structures = Evolution Programs 1992 Springer
21. F. Xhafa, J. Carretero, and A. Abraham Genetic algorithm based schedulers for grid computing systems Int. J. Innovative Comput. Inform. Control 3 5 2007 1053 1071
22. P.S. Mann Introductory Statistics seventh ed. 2010 Wiley
23. T. Grueninger Multimodal optimization using genetic algorithms, Technical Report 1997 Department of Mechanical Engineering, MIT Cambridge, MA
24. G. Katsaros, G. Gallizo, R. Kübert, T. Wang, J.O. Fitó, and D. Espling An integrated monitoring infrastructure for cloud environments Service Science: Research and Innovations in the Service Economy 2012 Springer 149 164 ISSN: 1865-4924
25. W.C. Chung, and R.S. Chang A new mechanism for resource monitoring in Grid computing Future Gener. Comput. Syst. 25 2009 1 7 10.1016/j.future.2008.04.008
26. V. Casolaa, A. Cuomob, M. Rakc, and U. Villanob The CloudGrid approach: security analysis and performance evaluation Future Gener. Comput. Syst. 29 2013 389 401 10.1016/j.future.2011.08.008
27. D. Zissis, and D. Lekkas Addressing cloud computing security issues Future Gener. Comput. Syst. 28 2012 583 592 10.1016/j.future.2010.12.006
28. M. Humphrey, M.R. Thompson, Security implications of typical grid computing usage scenarios, in: Proc. High Performance Distributed Computing, 2001.
29. V. Welch, F. Siebenlist, I. Foster, J. Bresnahan, K. Czajkowski, J. Gawor, C. Kesselman, S. Meder, L. Pearlman, S. Tuecke, Security for grid services, in: Proc. of Int. Symp. High Performance Distributed Computing, HPDC-12, 2003.
30. T. Xie, X. Qin, Enahancing security of real-time applications on grids through dynamic scheduling, in: Proc. of the 11th Workshop Job Scheduling Strategies for Parallel Processing, JSSPP2005, 2005, pp. 146-158.
31. K. Hwang, and Z. Xu Scalable Parallel Computing: Technology, Architecture, Programming 1998 McGraw-Hill San Francisco
32. K. Krauter, R. Buyya, and M. Maheswaran A taxonomy of grid resource management systems for distributed computing Softw. Pract. Exp. 32 2 2002 135 164
33. M. Maheswaran, S. Ali, H.J. Siegel, D. Hensgen, and R.F. Freund Dynamic mapping of a class of independent tasks onto heterogeneous computing systems J. Parallel Distrib. Comput. 59 1999 107 131
34. E. Cody, R. Sharman, R.H. Rao, and S. Upadhyaya Security in Grid computing: a review and synthesis Decis. Support Syst. 44 2008 749 764
35. S. Hwang, and C. Kesselman A flexible framework for fault tolerance in the grid J. Grid Comput. 1 3 2003 251 272
36. J. Abawajy An efficient adaptive scheduling policy for high performance computing Future Gener. Comput. Syst. 25 3 2009 364 370
37. Y.-K. Kwok, K. Hwang, and S. Song Selfish grids: game-theoretic modeling and NAS/PSA benchmark evaluation IEEE Trans. Parallel Distrib. Syst. 18 5 2007 1 16
38. C.-C. Wu, and R.-Y. Sun An integrated security-aware job scheduling strategy for large-scale computational grids Future Gener. Comput. Syst. 26 2010 198 206
39. Y. Gil, E. Deelman, J. Blythe, C. Kesselman, and H. Tangmunarunkit Artificial intelligence and grids: workflow planning and beyond IEEE Intell. Syst. 19 01 2004 26 33
40. K.-M. Yu, Z.-j. Luo, C.-H. Chou, C.-K. Chen, and J. Zhou A fuzzy neural network based scheduling algorithm for job assignment on computational grids T. Enokido, L. Barolli, M. Takizawa, Proc. of NBiS 2007 LNCS vol. 4658 2007 533 542
41. G. Zhao, Z. Shen, C. Miao, ELM-based intelligent resource selection for grid scheduling, in: Proc. of 2009 IEEE International Conference on Machine Learning and Applications, 2009, pp. 398-403.
42. T.V.T. Duy, Y. Sato, Y. Inoguchi, Performance evaluation of a Green Scheduling Algorithm for energy savings in Cloud computing, in: Proc. of 2010 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum, IPDPSW, 2010, pp. 1-8.