Secure scientific applications scheduling technique for cloud computing environment using global league championship algorithm

PLoS ONE

Volumn 11, Issue 7, 2016, Pages

  Abdulhamid, Shafi'i Muhammad ^a,b   Abd Latiff, Muhammad Shafie ^a   Abdul Salaam, Gaddafi ^c   Madni, Syed Hamid Hussain ^a  

^a UNIVERSITI TEKNOLOGI MALAYSIA   (Malaysia)

^b FEDERAL UNIVERSITY OF TECHNOLOGY   (Nigeria)

^c KWAME NKRUMAH UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Ghana)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; COMPUTER HEURISTICS; CONTROLLED STUDY; GENETIC ALGORITHM; GLOBAL LEAGUE CHAMPIONSHIP ALGORITHM; GLOBAL SCHEDULING; INFORMATION PROCESSING; MEASUREMENT ACCURACY; MEASUREMENT PRECISION; PROCESS OPTIMIZATION; SIMULATOR; ALGORITHM; CLOUD COMPUTING; COMPUTER SYSTEM; HOSPITAL MANAGEMENT; HUMAN; INFORMATION RETRIEVAL; INTERNET; PERSONNEL MANAGEMENT; PROBABILITY; STATISTICAL MODEL;

ALGORITHMS; APPOINTMENTS AND SCHEDULES; CLOUD COMPUTING; COMPUTER SYSTEMS; HUMANS; INFORMATION STORAGE AND RETRIEVAL; INTERNET; MODELS, STATISTICAL; PERSONNEL STAFFING AND SCHEDULING; PROBABILITY;

EID: 84978036271     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0158102     Document Type: Article

References (53)

1. Li J, Qiu M, Ming Z, Quan G, Qin X, Gu Z. (2012) Online optimization for scheduling preemptable tasks on IaaS cloud systems. Journal of Parallel and Distributed Computing 72: 666-677.
2. Abrishami S, Naghibzadeh M, Epema DH (2013) Deadline-constrained workflow scheduling algorithms for Infrastructure as a Service Clouds. Future Generation Computer Systems 29: 158-169.
3. Tsai C-W, Huang W-C, Chiang M-H, Chiang M-C, Yang C-S (2014) A hyper-heuristic scheduling algorithm for cloud. Cloud Computing, IEEE Transactions on 2: 236-250.
4. Achary R, Vityanathan V, Raj P, Nagarajan S (2015) Dynamic Job Scheduling Using Ant Colony Optimization for Mobile Cloud Computing. Intelligent Distributed Computing: Springer. pp. 71-82.
5. Alkhanak EN, Lee SP, Khan SUR (2015) Cost-aware challenges for workflow scheduling approaches in cloud computing environments: Taxonomy and opportunities. Future Generation Computer Systems.
6. Srikanth GU, Maheswari VU, Shanthi A, Siromoney A (2015) Task Scheduling Model. Indian Journal of Science and Technology 8: 33-42.
7. Madni SHH, Latiff MSA, Coulibaly Y (2016) An Appraisal of Meta-Heuristic Resource Allocation Techniques for IaaS Cloud. Indian Journal of Science and Technology 9.
8. Aceto G, Botta A, de Donato W, Pescapè A (2013) Cloud monitoring: A survey. Computer Networks.
9. Pan Y, Ding S, Fan W, Li J, Yang S (2015) Trust-Enhanced Cloud Service Selection Model Based on QoS Analysis. PLOS ONE 10.
10. Abdulhamid SM, Abd Latiff SM, Bashir MB (2014) Scheduling Techniques in On-Demand Grid as a Service Cloud: A Review. Journal of Theoretical & Applied Information Technology 63: 10-19.
11. El-Sisi AB, Tawfeek MA (2014) Cloud Task Scheduling for Load Balancing based on Intelligent Strategy. International Journal of Intelligent Systems and Applications (IJISA) 6: 25.
12. Frincu ME (2011) Adaptive Scheduling for Distributed Systems [PhD Thesis]: West University of Timisoara, Faculty of Mathematics and Computer Science, Department of Computer Science, Romania.
13. Shanahan HP, Owen AM, Harrison AP (2014) Bioinformatics on the cloud computing platform Azure.
14. Kashan HA. League championship algorithm: a new algorithm for numerical function optimization; 2009. IEEE. pp. 43-48.
15. Abdulhamid SM, Latiff MSA, Madni SHH, Oluwafemi O (2015) A Survey of League Championship Algorithm: Prospects and Challenges. Indian Journal of Science and Technology 8: 101-110.
16. Abdulhamid SM, Abd Latiff MS. League Championship Algorithm Based Job Scheduling Scheme for Infrastructure as a Service Cloud; 2014; Universiti Teknologi Malaysia, Johor Bahru, Malaysia. pp. 381-382.
17. Abdulhamid SM, Abd Latiff MS, Ismaila I (2014) Tasks scheduling technique using league championship algorithm for makespan minimization in IAAS cloud. ARPN Journal of Engineering and Applied Sciences 9: 2528-2533.
18. Kolodziej J, Khan SU, Xhafa F. Genetic algorithms for energy-aware scheduling in computational grids; 2011. IEEE. pp. 17-24.
19. Zhong SB, He ZS (2010) The Scheduling Algorithm of Grid Task Based on PSO and Cloud Model. Key Engineering Materials 439-440: 1487-1492.
20. Geng J, Huang M-L, Li M-W, Hong W-C (2015) Hybridization of seasonal chaotic cloud simulated annealing algorithm in a SVR-based load forecasting model. Neurocomputing 151: 1362-1373.
21. Beegom AA, Rajasree M (2015) Genetic Algorithm Framework for Bi-objective Task Scheduling in Cloud Computing Systems. Distributed Computing and Internet Technology: Springer. pp. 356-359.
22. Dutta D, Joshi R. A genetic: algorithm approach to cost-based multi-QoS job scheduling in cloud computing environment; 2011. ACM. pp. 422-427.
23. Yousif A, Abdullah AH, Nor SM, Bashir MB. Optimizing job scheduling for computational grid based on firefly algorithm; 2012. IEEE. pp. 97-101.
24. Gaior J, Seredyński F (2013) Multi-objective Parallel Machines Scheduling for Fault-Tolerant Cloud Systems. Algorithms and Architectures for Parallel Processing: Springer. pp. 247-256.
25. Hu X, Zhou X (2014) Ant colony algorithm based on dynamic trend prediction on scheduling optimization of cloud computing resources. Journal of Computational Information Systems 10: 8723-8730.
26. Sidhu J (2015) Ant Colony Optimization Algorithm For Independent Task Scheduling In Cloud Computing. International Journal of Applied Engineering Research 10.
27. Tawfeek M, El-Sisi A, Keshk AE, Torkey F. Cloud task scheduling based on ant colony optimization; 2015. IEEE. pp. 64-69.
28. Jin G, Liu L, Zhang P, Yu M (2015) Cost constrain load balanced ant colony scheduling of cloud environment. Journal of Information and Computational Science 12: 1045-1054.
29. Li K, Xu G, Zhao G, Dong Y, Wang D. Cloud task scheduling based on load balancing ant colony optimization; 2011. IEEE. pp. 3-9.
30. Yuan H, Li C, Du M (2014) Optimal Virtual Machine Resources Scheduling Based on Improved Particle Swarm Optimization in Cloud Computing. Journal of Software 9: 705-708.
31. Verma A, Kaushal S. Bi-Criteria Priority based Particle Swarm Optimization workflow scheduling algorithm for cloud; 2014. IEEE. pp. 1-6.
32. Ramezani F, Lu J, Hussain FK (2014) Task-Based System Load Balancing in Cloud Computing Using Particle Swarm Optimization. International Journal of Parallel Programming 42: 739-754.
33. Yang W, Zhang C, Shao Y, Shi Y, Li H, Khan M, et al. (2014) A Hybrid Particle Swarm Optimization Algorithm for Service Selection Problem in the Cloud. International Journal of Grid & Distributed Computing 7.
34. Wu K (2014) A Tunable Workflow Scheduling Algorithm Based on Particle Swarm Optimization for Cloud Computing
35. Zhang W, Xie H, Cao B, Cheng AM (2014) Energy-Aware Real-Time Task Scheduling for Heterogeneous Multiprocessors with Particle Swarm Optimization Algorithm. Mathematical Problems in Engineering 2014.
36. Rodriguez MA, Buyya R (2014) Deadline based resource provisioningand scheduling algorithm for scientific workflows on clouds. Cloud Computing, IEEE Transactions on 2: 222-235.
37. Pandey S, Wu L, Guru SM, Buyya R. A particle swarm optimization-based heuristic for scheduling workflow applications in cloud computing environments; 2010. IEEE. pp. 400-407.
38. Abdullahi M, Ngadi MA (2016) Symbiotic Organism Search optimization based task scheduling in cloud computing environment. Future Generation Computer Systems 56: 640-650.
39. Cheng M-Y, Prayogo D (2014) Symbiotic Organisms Search: A new metaheuristic optimization algorithm. Computers & Structures 139: 98-112.
40. Madni SHH, Latiff MSA, Coulibaly Y, Abdulhamid SM Resource Scheduling for Infrastructure as a Service (IaaS) in Cloud Computing: Challenges and Opportunities. Journal of Network and Computer Applications.
41. Guo-ning G, Ting-lei H, Shuai G. Genetic simulated annealing algorithm for task scheduling based on cloud computing environment; 2010. pp. 60-63.
42. Moschakis IA, Karatza HD (2013) Towards scheduling for Internet-of-Things applications on clouds: a simulated annealing approach. Concurrency and Computation: Practice and Experience.
43. Moharana SS, Ramesh RD, Powar D (2013) Analysis of load balancers in cloud computing. International Journal of Computer Science and Engineering 2: 101-108.
44. Mathew T, Sekaran KC, Jose J. Study and analysis of various task scheduling algorithms in the cloud computing environment; 2014. IEEE. pp. 658-664.
45. Bala A, Chana I (2015) Autonomic fault tolerant scheduling approach for scientific workflows in Cloud computing. Concurrent Engineering: 1063293X14567783.
46. Smanchat S, Viriyapant K (2015) Taxonomies of workflow scheduling problem and techniques in the cloud. Future Generation Computer Systems 52: 1-12.
47. Zhan Z-H, Liu X-F, Gong Y-J, Zhang J, Chung HS-H, Li Y. Cloud computing resource scheduling and a survey of its evolutionary approaches. ACM Computing Surveys (CSUR). 2015; 47(4):63.
48. Yazar S, Gooden GE, Mackey DA, Hewitt AW (2014) Benchmarking undedicated cloud computing providers for analysis of genomic datasets.
49. Hazlewood V (2015) Parallel Workload Archive - SDSC-SP2-1998-4.swf.
50. Chen Z-G, Du K-J, Zhan Z-h, Zhang J, editors. Deadline constrained cloud computing resources scheduling for cost optimization based on dynamic objective genetic algorithm. Evolutionary Computation (CEC), 2015 IEEE Congress on; 2015: IEEE.
51. Liu X-F, Zhan Z-H, Du K-J, Chen W-N, editors. Energy aware virtual machine placement scheduling in cloud computing based on ant colony optimization approach. Proceedings of the 2014 conference on Genetic and evolutionary computation; 2014: ACM.
52. Madni SHH, Latiff MSA, Coulibaly Y. Resource scheduling for infrastructure as a service (IaaS) in cloud computing: Challenges and opportunities. Journal of Network and Computer Applications. 2016; 68:173-200.
53. Li H-H, Chen Z-G, Zhan Z-H, Du K-J, Zhang J, editors. Renumber coevolutionary multiswarm particle swarm optimization for multi-objective workflow scheduling on cloud computing environment. Proceedings of the Companion Publication of the 2015 on Genetic and Evolutionary Computation Conference; 2015: ACM.