Swarm scheduling approaches for work-flow applications with security constraints in distributed data-intensive computing environments

Information Sciences

Volumn 192, Issue , 2012, Pages 228-243

  Liu, Hongbo ^a,b,c   Abraham, Ajith ^c,d   Snášel, Václav ^c,d   McLoone, Seán ^e  

^a DALIAN MARITIME UNIVERSITY   (China)

^b DALIAN UNIVERSITY OF TECHNOLOGY   (China)

^c SCIENTIFIC NETWORK FOR INNOVATION AND RESEARCH EXCELLENCE   (United States)

^d VSB TECHNICAL UNIVERSITY OF OSTRAVA   (Czech Republic)

^e NATIONAL UNIVERSITY OF IRELAND   (Ireland)

Author keywords

Distributed data intensive computing environments; Particle swarm; Scheduling problem; Security constraints; Swarm intelligence; Work flow

Indexed keywords

DATA-INTENSIVE COMPUTING; PARTICLE SWARM; SCHEDULING PROBLEM; SECURITY CONSTRAINT; SWARM INTELLIGENCE; WORK-FLOWS;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; PARTICLE SWARM OPTIMIZATION (PSO); SCHEDULING;

COMPUTER SYSTEMS;

EID: 84862777930     PISSN: 00200255     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ins.2011.12.032     Document Type: Article

References (62)

1. A. Abraham, H. Guo, and H. Liu Swarm intelligence: foundations, perspectives and applications Swarm Intelligent Systems, Studies in Computational Intelligence 26 2006 3 25 (Pubitemid 44781513)
2. M.R. AlRashidi, and M.E. El-Hawary A survey of particle swarm optimization applications in electric power systems IEEE Transactions on Evolutionary Computation 13 4 2009 913 918
3. I. Babaoglu, O. Findik, and E. lker A comparison of feature selection models utilizing binary particle swarm optimization and genetic algorithm in determining coronary artery disease using support vector machine Expert Systems with Applications 37 4 2010 3177 3183
4. K. Binkley, and M. Hagiwara Balancing exploitation and exploration in particle swarm optimization: velocity-based reinitialization Information and Media Technologies 3 1 2008 103 111
5. A. Boccia, G. Busiello, L. Milanesi, and G. Paolella A fast job scheduling system for a wide range of bioinformatic applications IEEE Transactions on NanoBioscience 6 2 2007 149 154 (Pubitemid 46883420)
6. D. Boeringer, and D. Werner Particle swarm optimization versus genetic algorithms for phased array synthesis IEEE Transactions on Antennas and Propagation 52 3 2004 771 779
7. P. Brucker Scheduling Algorithms 2007 Springer Verlag
8. R. Chang, J. Chang, and P. Lin An ant algorithm for balanced job scheduling in grids Future Generation Computer Systems 25 1 2009 20 27
9. K. Chung, and P. Erdös On the application of the Borel-Cantelli lemma Transactions of the American Mathematical Society 72 1952 179 186
10. S. Chung, F. Chan, and H. Chan A modified genetic algorithm approach for scheduling of perfect maintenance in distributed production scheduling Engineering Applications of Artificial Intelligence 22 7 2009 1005 1014
11. M. Clerc Particle Swarm Optimization 2006 ISTE Publishing Company
12. M. Clerc, and J. Kennedy The particle swarm-explosion, stability, and convergence in a multidimensional complex space IEEE Transactions on Evolutionary Computation 6 1 2002 58 73 (Pubitemid 34404564)
13. S. Das, A. Abraham, and A. Konar Automatic kernel clustering with a multi-elitist particle swarm optimization algorithm Pattern Recognition Letters 29 5 2008 688 699
14. F. Dong, S. Akl, Scheduling Algorithms for Grid Computing: State of the Art and Open Problems, Tech. Rep., School of Computing, Queen's University, Kingston, Ontario, January 2006.
15. R. Eberhart, and Y. Shi Comparison between genetic algorithms and particle swarm optimization Lecture Notes in Computer Science 1447 1998 611 618 (Pubitemid 128118971)
16. A. Engelbrecht Fundamentals of Computational Swarm Intelligence 2005 Wiley London
17. S. Ghosh, D. Kundu, K. Suresh, S. Das, A. Abraham, B. Panigrahi, V. Snášel, On some properties of the lbest topology in particle swarm optimization, in: Proceedings of the 2009 Ninth International Conference on Hybrid Intelligent Systems, vol. 3, IEEE Computer Society Press, Washington, 2009, pp. 370-375.
18. C. Guo, and H. Tang Global convergence properties of evolution stragtegies Mathematica Numerica Sinica 23 1 2001 105 110
19. P. Hansen, and N. Mladenović Variable neighborhood search: principles and applications European Journal of Operational Research 130 3 2001 449 467 (Pubitemid 32875304)
20. P. Hansen, N. Mladenović, and J. Moreno Pérez Variable neighbourhood search: methods and applications Annals of Operations Research 175 1 2010 367 407
21. P. Hansen, N. Mladenović, and D. Urošević Variable neighborhood search and local branching Computers and Operations Research 33 10 2006 3034 3045 (Pubitemid 43199839)
22. R. He, Y. Wang, Q. Wang, J. Zhou, and C. Hu Improved particle swarm optimization based on self-adaptive escape velocity Chinese Journal of Software 16 12 2005 2036 2044
23. T. Hey, S. Tansley, and K. Tolle The fourth paradigm: data-intensive scientific discovery Microsoft Research 2009
24. W. Horn AI in medicine on its way from knowledge-intensive to data-intensive systems Artificial Intelligence in Medicine 23 1 2001 5 12 (Pubitemid 32677974)
25. M. Jiang, Y. Luo, and S. Yang Stochastic convergence analysis and parameter selection of the standard particle swarm optimization algorithm Information Processing Letters 102 1 2007 8 16 (Pubitemid 46186357)
26. V. Kadirkamanathan, K. Selvarajah, and P. Fleming Stability analysis of the particle dynamics in particle swarm optimizer IEEE Transactions on Evolutionary Computation 10 3 2006 245 255 (Pubitemid 43821758)
27. J. Kennedy, R. Eberhart, and Y. Shi Swarm Intelligence 2001 Springer
28. J. Kennedy, R. Mendes, Population structure and particle swarm performance, in: Proceedings of the Evolutionary Computation on Evolutionary Computation, 2002, pp. 1671-1676.
29. B. Khoo, B. Veeravalli, T. Hung, and C. See A multi-dimensional scheduling scheme in a grid computing environment Journal of Parallel and Distributed Computing 67 6 2007 659 673 (Pubitemid 46671486)
30. A. Lazinica Particle Swarm Optimization 2009 InTech Education and Publishing
31. J. Lee, B. Tierney, and W. Johnston Data intensive distributed computing: a medical application example Lecture Notes in Computer Science 1593 1999 150 158
32. H. Liu, and A. Abraham An hybrid fuzzy variable neighborhood particle swarm optimization algorithm for solving quadratic assignment problems Journal of Universal Computer Science 13 9 2007 1309 1331
33. H. Liu, A. Abraham, and M. Clerc Chaotic dynamic characteristics in swarm intelligence Applied Soft Computing 7 3 2007 1019 1026 (Pubitemid 46551940)
34. H. Liu, A. Abraham, and Z. Wang A multi-swarm approach to multi-objective flexible job-shop scheduling problems Fundamenta Informaticae 95 2009 1 25
35. H. Liu, B. Li, Y. Ji, and T. Sun Particle swarm optimisation from lbest to gbest Applied Soft Computing Technologies: The Challenge of Complexity 34 2006 537 545 (Pubitemid 44896247)
36. N. Liu, M. Abdelrahman, and S. Ramaswamy A complete multiagent framework for robust and adaptable dynamic job shop scheduling IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews 37 5 2007 904 916 (Pubitemid 47323560)
37. J. Martínez, and E. Gonzalo The generalized PSO: a new door to PSO evolution Journal of Artificial Evolution and Applications 2008 2008 1 15
38. G. Mosheiov, and A. Sarig Scheduling with a common due-window: polynomially solvable cases Information Sciences 180 8 2010 1492 1505
39. K. Parsopoulos, and M. Vrahatis Recent approaches to global optimization problems through particle swarm optimization Natural Computing 1 2 2002 235 306
40. K. Ranganathan, and I. Foster Decoupling computation and data scheduling in distributed data-intensive applications Proceedings of the 11th International Symposium on High Performance Distributed Computing 2002 IEEE Computer Society Press Washington 352 361
41. V. Roshanaei, B. Naderi, F. Jolai, and M. Khalili A variable neighborhood search for job shop scheduling with set-up times to minimize makespan Future Generation Computer Systems 25 6 2009 654 661
42. Y. Shi, R. Eberhart, E. Team, I. Kokomo, Fuzzy adaptive particle swarm optimization, in: Proceedings of the 2001 Congress on Evolutionary Computation, vol. 1, 2001, pp. 101-106. (Pubitemid 32806325)
43. S. Song, K. Hwang, and Y. Kwok Risk-resilient heuristics and genetic algorithms for security-assured grid job scheduling IEEE Transactions on Computers 55 6 2006 703
44. S. Song, K. Hwang, R. Zhou, and Y. Kwok Trusted P2P transactions with fuzzy reputation aggregation IEEE Internet Computing 9 6 2005 24 34 (Pubitemid 43051365)
45. S. Song, Y. Kwok, and K. Hwang Security-driven heuristics and a fast genetic algorithm for trusted grid job scheduling Proceedings of the 19th International Parallel and Distributed Processing Symposium vol. 65 2005 IEEE Computer Society Washington, DC, USA 4 12
46. S. Sundar, and A. Singh A swarm intelligence approach to the quadratic minimum spanning tree problem Information Sciences 180 17 2010 3182 3191
47. Y. Tao, H. Jin, X. Shi, Grid workflow scheduling based on reliability cost, in: Proceedings of the 2nd International Conference on Scalable Information Systems, ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering), Brussels, Belgium, Belgium, 2007.
48. I. Trelea The particle swarm optimization algorithm: convergence analysis and parameter selection Information Processing Letters 85 6 2003 317 325
49. F. Van den Bergh, An analysis of particle swarm optimizers, Ph.D. thesis, University of Pretoria, Pretoria, South Africa, November 2001.
50. F. Van den Bergh, and A. Engelbrecht A study of particle swarm optimization particle trajectories Information Sciences 176 8 2006 937 971 (Pubitemid 43190068)
51. S. Venugopal, and R. Buyya A deadline and budget constrained scheduling algorithm for eScience applications on data grids Lecture Notes in Computer Science 3719 2005 60 72
52. S. Venugopal, and R. Buyya An SCP-based heuristic approach for scheduling distributed data-intensive applications on global grids Journal of Parallel and Distributed Computing 68 4 2008 471 487 (Pubitemid 351296392)
53. Y. Wen, H. Xu, and J. Yang A heuristic-based hybrid genetic-variable neighborhood search algorithm for task scheduling in heterogeneous multiprocessor system Information Sciences 181 3 2011 567 581
54. C. Wu, and R. Sun An integrated security-aware job scheduling strategy for large-scale computational grids Future Generation Computer Systems 26 2 2010 198 206
55. T. Xie, and X. Qin Scheduling security-critical real-time applications on clusters IEEE Transactions on Computers 55 7 2006 864 879 (Pubitemid 43834519)
56. T. Xie, and X. Qin Performance evaluation of a new scheduling algorithm for distributed systems with security heterogeneity Journal of Parallel and Distributed Computing 67 10 2007 1067 1081 (Pubitemid 47333349)
57. T. Xie, and X. Qin Security-driven scheduling for data-intensive applications on grids Cluster Computing 10 2 2007 145 153 (Pubitemid 46767522)
58. C. Yu, and D. Marinescu Algorithms for divisible load scheduling of data-intensive applications Journal of Grid Computing 2009 1 23
59. Z. Zhan, J. Zhang, Y. Li, and H. Chung Adaptive particle swarm optimization IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 39 6 2009 1362 1381
60. R. Zhang, and C. Wu A hybrid immune simulated annealing algorithm for the job shop scheduling problem Applied Soft Computing 10 1 2010 79 89
61. X. Zhao A perturbed particle swarm algorithm for numerical optimization Applied Soft Computing 10 1 2010 119 124
62. N. Zhong, J. Hu, S. Motomura, J. Wu, and C. Liu Building a data-mining grid for multiple human brain data analysis Computational Intelligence 21 2 2005 177 196 (Pubitemid 40557925)