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A Survey of Workflow Scheduling Algorithms and Research Issues

by Lovejit Singh, Sarbjeet Singh
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 74 - Number 15
Year of Publication: 2013
Authors: Lovejit Singh, Sarbjeet Singh
10.5120/12961-0069

Lovejit Singh, Sarbjeet Singh . A Survey of Workflow Scheduling Algorithms and Research Issues. International Journal of Computer Applications. 74, 15 ( July 2013), 21-28. DOI=10.5120/12961-0069

@article{ 10.5120/12961-0069,
author = { Lovejit Singh, Sarbjeet Singh },
title = { A Survey of Workflow Scheduling Algorithms and Research Issues },
journal = { International Journal of Computer Applications },
issue_date = { July 2013 },
volume = { 74 },
number = { 15 },
month = { July },
year = { 2013 },
issn = { 0975-8887 },
pages = { 21-28 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume74/number15/12961-0069/ },
doi = { 10.5120/12961-0069 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:42:22.410168+05:30
%A Lovejit Singh
%A Sarbjeet Singh
%T A Survey of Workflow Scheduling Algorithms and Research Issues
%J International Journal of Computer Applications
%@ 0975-8887
%V 74
%N 15
%P 21-28
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Cloud Computing refers to a paradigm whereby services are offered via internet using pay as you go model. Services are deployed in data centers and the pool of data centers is collectively referred to as "Cloud". Data centers make use of scheduling techniques to optimally allocate resources to various jobs. Different scenarios require different scheduling algorithms. The selection of a particular scheduling algorithm depends upon various factors like the parameter to be optimized (cost or time), quality of service to be provided and information available regarding various aspects of job. Workflow applications are the applications which require various sub-tasks to be executed in a particular fashion in order to complete the whole task. These tasks have parent child relationship. The parent task needs to be executed before its child task. Workflow scheduling algorithms are supposed to preserve dependency constraints implied by their nature and structure. Resources are allocated to various sub-tasks of the original task by keeping into account these constraints. In this paper, various workflow scheduling algorithms have been surveyed. Some algorithms have been found to optimize cost, some have been found to optimize time, some focuses on reliability, some focuses on availability, some focuses on energy efficiency, some focuses on load balancing or some focuses on a combination of these parameters. A lot of work has already been done in the area of workflow scheduling but still, we feel that there is a need and lot of scope in applying other optimization techniques, like intelligent water drops, to schedule workflow applications.

References
  1. Rajkumar Buyya, Chee Shin Yeo, Srikumar Venugopal, James Broberg, and Ivona Brandic. 2009. Cloud Computing and Emerging IT Platforms: Vision, Hype, and Reality for Delivering Computing as the 5th Utility. Journal Future Generation Computer Systems Archive, vol. 25, pp. 599-616, Elsevier Science Publisher.
  2. Y. Du and X. Li. 2008. Application of Workflow Technology to Current Dispatching Order System. International Journal of Computer Science and Network Security, 8(3), 59-61.
  3. R. Allen. 2001. Workflow: an Introduction Workflow Management Coalition, Workflow Handbook.
  4. Jia Yu, Raj Kumar Buyya and Kotagiri Ramamohanarao. 2008. Workflow Scheduling Algorithm for Grid Computing. Meta-heuristics for Scheduling in Distributed Computing Environment, Vol. 146, Pg. 173-214, Springer Berlin Heidelberg.
  5. Rizos Sakellariou and Henan Zhao. 2004. Hybrid Heuristic for DAG Scheduling on Heterogeneous Systems. Parallel and Distributed Processing Symposium, 18th IEEE International Conference.
  6. A. Mandal, K. Kennedy, C. Koelbel, G. Marin, J. Crummey and B. Liu. 2005. Scheduling Strategies for Mapping Application Workflows onto the Grid. High Performance Distributed Computing, 14th IEEE International Conference.
  7. Marek Wieczorek, Radu Prodan and Thomas Fahringer. 2005. Scheduling of Scientific Workflows in the ASKALON Grid Environment. ACM SIGMOD, Vol. 34, Issue 3, Pg. 56-62.
  8. Jia Yu and Raj Kumar Buyya. 2006. A Budget Constrained Scheduling of Workflow Applications on Utility Grids using Genetic Algorithms. Workflows in Support of Large-Scale Science, IEEE Conference, Pg. 1-10.
  9. Jai YU and Raj Kumar Buyya. 2006. Scheduling Scientific Workflow Applications with Deadline and Budget Constraints using Genetic Algorithms. Scientific Programming Journal, Pg. 217-230, Vol. 14, Issue 3-4.
  10. M. Rahman, S. Venugopal and R. Buyya. 2007. A Dynamic Critical Path Algorithm for Scheduling Scientific Workflow Applications on Global Grids. E-Science and Grid Computing, IEEE International Conference, Pg. 35-42.
  11. Wei Neng Chen, Jun Zhang and Yang Yu. 2007. Workflow Scheduling in Grids: an ant colony optimization approach. Evolutionary Computation, IEEE Conference, Pg. 3308-3315.
  12. Bogdan Simion, Catalin Leordeanu, Florin Pop and Valentin Cristea. 2007. A Hybrid Algorithm for Scheduling Workflow Applications in Grid Environments. OTM Confederated International Conferences, Pg. 1331-1348, Springer Berlin Heidelberg.
  13. Fli Tao, Dongming Zhao, Yefa Hu and Zude Zhou. 2008. Resource Service Composition and Its Optimal Selection Based on Particle Swarm Optimization in Manufacturing Grid System. Industrial Informatics, IEEE Transactions, Pg. 315-327.
  14. A. K. M Khaled , Michael Kirley and Raj Kumar Buyya. 2009. Multi-Objective Differential Evolution for Scheduling Workflow Applications on Global Grids. Journal Concurrency and Computation: Practice and Experience, Vol. 21, Issue 13.
  15. Wei Neng Chena and Jun Zhang. 2009. An Ant Colony Optimization Approach to a Grid Workflow Scheduling Problem with Various QoS Requirements. System, Man and Cybernetics, Applications and Reviews, IEEE Transactions, Vol. 39, Issue 1, Pg. 29-43.
  16. Qian Tao, Hui You Chang, Yang Yi, Chunqin Gu and Yang Yu. 2009. QoS Constrained Grid Workflow Scheduling Optimization Based on a Novel PSO Algorithm, Grid and Cooperative Computing. 8th IEEE International Conference, Pg. 153-159.
  17. Yanli Hu, Lining Xing, Weiming Zhang, Weidong Xiao and Daquan Tang. 2010. A Knowledge Based Ant Colony Optimization for a Grid Workflow Scheduling Problem. First International Conference Beijing, China, Pg. 241-248, Springer Berlin Heidelberg.
  18. Suraj Pandy, Linlin Wu, Siddeshwara Mayura Guru and Raj Kumar Buyya. 2010. A Particle Swarm Optimization-Based Heuristic for Scheduling Workflow Application in Cloud Computing Environments. Advance Information Networking and Applications, IEEE International Conference, Pg. 400-407.
  19. Zhangjun Wu, Zhiwei Ni, Lichuan Gu and Xiao Liu. 2010. A Revised Discrete Particle Swarm Optimization for Cloud Workflow Scheduling. Computational Intelligence and Security IEEE International Conference, Pg. 184-188.
  20. Yong Wang, R. M. Bhati and M. A. Bauer. 2011. A Novel Deadline and Budget Constrained Scheduling Heuristic for Computation Grids. Journal of Central South University of Technology Vol. 18, Issue 2, Pg. 465-472.
  21. Sawant Shailesh. 2011. A Genetic Algorithm Scheduling Approach for Virtual Machine Resource in a Cloud Computing Environment. Master's Project.
  22. F. Coutinho, L. A. V. Decarvalho and R. Santana. 2011. A Workflow Scheduling Algorithm for Optimizing Energy Efficient Grid Resources Usage, Dependable. Automic and Secure Computing, 9th IEEE International Conference, Pg. 642-649.
  23. Xiaofeng Wang, Chee Shin Yeo, Raj Kumar Buyya and Jinshu Su. 2011. Optimizing the Makespan and Reliability for Workflow Applications with Reputation and a Look-ahead Genetic Algorithm. Journal Future Generation Computer Systems, Vol. 27, Issue 8, Pg. 1124-1134.
  24. Eugen Feller, Louis Rilling and Christine Morin. 2011. Energy-Aware Ant Colony Based Workload Placement in Clouds, Grid Computing. 12th IEEE International Conference, Pg. 26-33.
  25. Rajarathinam Jeyarani, N. Nagaveni and Vasanth Ram. 2011. Self Adaptive Particle Swarm Optimization for Efficient Virtual Machine Provisioning in Cloud. International Journal of Intelligent Information Technologies, Vol. 7, Issue 2.
  26. Saurabh Kumar Garg, Parmod Konugurthi and Raj Kumar Buyya. 2011. A Linear Programming Driven Genetic Algorithm for Meta-Scheduling on Utility Grids. International Journal of Parallel, Emergent and Distributed Systems, Vol. 26, Issue 6.
  27. Jiandun Li, Junjie Peng, Zhou Lei and Wu Zhang. 2011. An Energy Efficient Scheduling Approach Based on Private Clouds. Journal of Information and Computational Science, Pg. 716-724.
  28. H. M. Fard, R. Prodan, J. J. D Barrionuevo and T. Fahringer. 2012. A Multi-Objective Approach for Workflow Scheduling in Heterogeneous Environment. Cluster, Cloud and Grid Computing 12th IEEE International Conference, Pg. 300-309.
  29. Timur Keskinturk, Mehmet B. Yildirim and Mehmet Barut. 2012. An Ant Colony Optimization Algorithm for Load Balancing in Parallel Machines with Sequence-Dependent Setup Times. Computer and Operations Research, Vol. 39, Issue 6, Pg. 1225-1235.
  30. S. H. Niu, S. K. Ong and A. Y. C Nee. 2012. An Improved Intelligent Water Drops Algorithm for Achieving Optimal Job Shop Scheduling Solution. International Journal of Production Research, Vol. 50, Issue 15.
  31. Saeid Abrishami, Mahmoud Naghibzadeh and Dick H. J. E Pema. 2013. Deadline-Constrained Workflow Scheduling Algorithm for Infrastructure as a Service. Journal Future Generation Computer Systems, Vol. 29, Issue 1, Pg. 158-169.
  32. Zhangjun Wu, Xiao Liu, Zhiwei Ni Dong Yuan and Yun Yang. 2013. A Market Oriented Hierarchical Scheduling Strategy in Cloud Workflow Systems. The Journal of Super Computing, Vol. 63, Issue 1, Pg. 256-293, Springer US.
  33. Simrat Kaur and Sarbjeet Singh. 2012. Comparative Analysis of Job Grouping Based Scheduling Strategies in Grid Computing. International Journal of Computer Applications, Vol. 43, Issue 15.
Index Terms

Computer Science
Information Sciences

Keywords

Cloud computing workflow applications workflow scheduling algorithms intelligent water drops based algorithm

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