Huimin Luo^1,2, Chaokun Yan This email address is being protected from spambots. You need JavaScript enabled to view it.¹ and Zhigang Hu²

¹School of Computer and Information Engineering, Henan University, Kaifeng, P.R. China
²School of Information Science and Engineering, Central South University, Changsha, P.R. China

REFERENCES

1. [1] Gentzsch, W., Girou, D., Kennedy, A., et al., “DEISADistributed European Infrastructure for Supercomputing Applications,” Journal of Grid Computing, Vol. 9, No. 2, pp. 259277 (2011). doi: 10.1007/s10723-011-9183-2
2. [2] Iosup, A., Dumitrescu, C., Epema, D. H. J., Li, H. and Wolters, L., “How are Real Grids Used? The Analysis of Four Grid Traces and Its Implications,” Proc. of 2006 IEEE/ACM International Conference on Grid Computing, Barcelona, Spain, Sep. 2829, pp. 262 269 (2006). doi: 10.1109/ICGRID.2006.311024
3. [3] Information on http://aws.amazon.com/ec2/
4. [4] Information on http://www.eucalyptus.com/
5. [5] Menasc, D. A. and Casalicchio, E., “A Framework for Resource Allocation in Grid Computing,” Proc. of 2004 International Workshop on Modeling, Analysis, and Simulation of Computer and Telecommunications Systems, Vollendam, The Netherlands, pp. 259267 (2004). doi: 10.1109/MASCOT.2004.1348280
6. [6] Tsiakkouri, H. Z. E., Sakellariou, R. and Dikaiakos, M. D., “Scheduling Workflows with Budget Constraints,” Proc. of 2005 CoreGRID Workshop Integrated Research in Grid Computing, Pisa, Italy Gorlatch, Nov. 2830, pp. 347357 (2005). doi: 10.1007/978-0-387-47658-2_14
7. [7] Yu, J. and Buyya, R., “A Budget Constrained Scheduling of Workflow Applications on Utility Grids Using Genetic Algorithms,” Proc. of 2006 IEEE International Symposium on High Performance Distributed Computing, Paris, France, Jun. 1923, pp. 1923 (2006). doi: 10.1109/WORKS.2006.5282330
8. [8] Xu, M., Cui, L., Wang, H. and Bi, Y., “A Multiple QoS Constrained Scheduling Strategy of Multiple Workflows for Cloud Computing,” Proc. of IEEE Symposium on Parallel and Distributed Processing with Applications, Aug. 912, Chengdu, China, pp. 629 ! "#$$%&' doi: 10.1109/ISPA.2009.95
9. [9] Abrishami, S. and Naghibzadeh, M., “Deadline-Constrained Workflow Scheduling in Software as a Service Cloud,” Scientia Iranica, Transactions D: Computer Science and Engineering and Electrical Engineering, pp. 680689 (2012). doi: 10.1016/j.scient.2011.11.047
10. [10] Dong, F. and Akl, S. G., “PFAS: A Resource-Performance-Fluctuation-Aware Workflow Scheduling Strategies for Grid Computing,” Proc. of IEEE Symposium on Parallel and Distributed Processing, Mar. 2630, Long Beach, California, pp. 19 (2007). doi: 10.1109/ IPDPS.2007.370328
11. [11] Zhao, H. and Sakellariou, R., “Advance Reservation Policies for Workflows,” Proc. of 2007 Workshop on Job Scheduling Strategies for Parallel Processing, Jun. 17, Seattle, WA, USA, pp. 4667 (2007). doi: 10. 1007/978-3-540-71035-6_3
12. [12] Wieczorek, M., Siddiqui, M., Villazón, A., Prodan, R. and Fahringer, T., “Applying Advance Reservation to Increase Predictability of Workflow Execution on the Grid,” Proc. of 2006 E-Science and Grid Computing Conference, Dec. 46, Amsterdam, The Netherlands, p. 82 (2006). doi: 10.1109/E-SCIENCE.2006.261166
13. [13] Information on http://www.opennebula.org/doku.php
14. [14] Deelman, E., Singh, G., Livny, M., Berriman, B. and Good, J., “The Cost of Doing Science on the Cloud: The Montage Example,” Proc. of ACM/IEEE Supercomputing Conference, Nov. 1521, Austin, Texas, USA, pp. 112 (2008). doi: 10.1109/SC.2008.5217932
15. [15] Kim, H., Khamra, Y. el, Rodero, I., Jha, S. and Parashar, M., “Autonomic Management of Application Workflows on Hybrid Computing Infrastructure,” Scientific Programming, Vol. 19, No. 2, pp. 7589 (2011).
16. [16] Ostermann, S., Prodan, R. and Fahringer, T., Cloud Computing: Computer Communications and Networks, Springer Press, Berlin, pp. 179184 (2010). doi: 10. 1007/978-1-84996-241-4_11
17. [17] Bittencourt, L. F., Senna, C. R. and Madeira, E. R. M., “Enabling Execution of Service Workflows in Grid/ Cloud Hybrid Systems,” Proc. of 2010 IEEE Symposium on Network Operations and Management Symposium, Apr. 1923, Osaka, Japan, pp. 343349 (2010). doi: 10.1109/NOMSW.2010.5486553
18. [18] Ramakrishnan, L., Koelbel, C., Kee, Y., Wolski, R., Nurmi, D., Gannon, D., Obertelli, G., YarKhan, A., Mandal, A., Huang, T. M., Thyagaraja, K. and Zagorodnov, D., “VGrADS: Enabling E-Science Workflows on Grids and Clouds with Fault Tolerance,” Proc. of 2009 ACM/IEEE Conference on High Performance Computing, Networking, Storage and Analysis, Nov. 1420, Portland, OR, USA, pp. 369376 (2009). doi: 10.1145/1654059.1654107
19. [19] Nurmi, D., Brevik, J. and Wolski, R., “QBETS: Queue Bounds Estimation from Time Series,” Proc. of 2007 ACM International Conference on Measurement and Modeling of Computer Systems, Jun. 1216, San Diego, CA, USA, pp. 379380 (2007). doi: 10.1145/125 4882.1254939
20. [20] Vecchiola, C., Calheiros, R. N., Karunamoorthy, D. and Buyya, R., “Deadline-Driven Provisioning of Resources for Scientific Applications in Hybrid Clouds with Aneka,” Future Generation Computer Systems, Vol. 28, No. 1, pp. 5865 (2012). doi: 10.1016/j.future. 2011.05.008
21. [21] Bittencourt, L. F., Senna, C. R. and Madeira, E. R. M., “HCOC: a Cost Optimization Algorithm for Workflow Scheduling in Hybrid Clouds,” Journal of Internet Services and Applications, Vol. 2, No. 3, pp. 207227 (2012). doi: 10.1007/s13174-011-0032-0
22. [22] Liu, X., Yang, Y., Jiang Y. C. and Chen, J. J., “Preventing Temporal Violations in Scientific Workflows: Where and How,” Transactions on Software Engineering, Vol. 37, No. 6, pp. 805825 (2010). doi: 10. 1109/TSE.2010.99
23. [23] Iosup, A., Jan, M., Sonmez, O. O. and Epema, D. H. J., “The Characteristics and the Performance of Groups of Jobs in Grids,” Lecture Notes on Computer Science, Vol. 4641, pp. 382393 (2007). doi: 10.1007/978-3- 540-74466-5_42
24. [24] Information on http://aws.amazon.com/ec2/
25. [25] Jøsang, A. and Haller, J., “Dirichlet Reputation Systems,” Proc. of 2007 International Conference on Availability, Reliability and Security, Vienna, Austria, Apr. 1013, pp. 112119 (2007). doi: 10.1109/ARES.2007.71
26. [26] Wang, X., Ding, L. and Bi, D. W., “Reputation-Enabled Self-Modification for Target Sensing in Wireless Sensor Networks,” IEEE Transactions on Instrumentation and Measurement, Vol. 59, No. 1, pp. 171179 (2010). doi: 10.1109/TIM.2009.2022445
27. [27] Deelman, E., Singh, G., Su, M. H., Blythe, J., Gil, Y., Kesselman, C., Mehta, G., Vahi, K., Berriman, G. B., Good, J., Laity, A., Jacob, J. C. and Katz, D. S., “Pegasus: a Framework for Mapping Complex Scientific Workflows onto Distributed System,” Scientific Programming Journal, Vol. 13, No. 3, pp. 219237 (2005).
28. [28] Yu, J., Buyya, R. and Tham, C. K., “Cost-Based Scheduling of Scientific Workflow Applications on Utility Grids,” Proc. of 2005 International Conference on E-Science and Grid Computing, July 58, Melbourne, Australia, pp. 140147 (2005). doi: 10.1109/ E-SCIENCE.2005.26
29. [29] Yuan, Y. C., Li, X. P., Wang, Q. and Zhu, X., “Deadline Division-Based Heuristic for Cost Optimization in Workflow Scheduling,” Information Science, Vol. 179, No. 15, pp. 25622575 (2009). doi: 10.1016/j. ins.2009.01.035
30. [30] Information on http://www.cloudbus.org
31. [31] Information on https://www.grid5000.fr/
32. [32] Juve, G., Chervenak, A., Deelman, E., et al., “Characterization and Profiling Scientific Workflows,” Future Generation Computation Systems, Vol. 29, No. 3, pp. 682692 (2013). doi: 10.1016/j.future.2012.08.015
33. [33] Yeo, C. S. and Buyya, R., “Pricing for Utility-Driven Resource Management and Allocation in Clusters,” International Journal of High Performance Computing Applications, Vol. 21, No. 4, pp. 405418D (2007). doi: 10.1177/1094342007083776