Journal of Soft Computing Paradigm
IRO Journals
Volume 1 — Issue 1 — September 2019

A STOCHASTIC DEVELOPMENT OF CLOUD COMPUTING BASED TASK SCHEDULING ALGORITHM

https://doi.org/10.36548/jscp.2019.1.005
V. Karunakaran
Department of Computer Sciences Technology, Karunya Institute of Technology and Sciences, Coimbatore, India
PDF
PDF

How to Cite

Karunakaran, V. 2019. “A STOCHASTIC DEVELOPMENT OF CLOUD COMPUTING BASED TASK SCHEDULING ALGORITHM”. Journal of Soft Computing Paradigm 1 (1): 41-48. https://doi.org/10.36548/jscp.2019.1.005.
ACM ACS APA ABNT Chicago Harvard IEEE MLA Turabian Vancouver AMA

Download Citation

Endnote/Zotero/Mendeley (RIS) BibTeX

Keywords

— NSGA
— Cloud Computing
— GSA
— Task Scheduling
— Virtual Machine
Published: 30-09-2019

Abstract

Due to diversity of services with respect to technology and resources, it is challenging to choose virtual machines (VM) from various data centres with varied features like cost minimization, reduced energy consumption, optimal response time and so on in cloud Infrastructure as a Service (IaaS) environment. The solutions available in the market are exhaustive computationally and aggregates multiple objectives to procure single trade-off that affects the solution quality inversely. This paper describes a hybrid algorithm that facilitates VM selection for scheduling applications based on Gravitational Search and Non-dominated Sorting Genetic Algorithm (GSA and NSGA). The efficiency of the proposed algorithm is verified by the simulation results.

References

  1. Al-Maamari, Ali, and Fatma A. Omara. "Task scheduling using PSO algorithm in cloud computing environments." International Journal of Grid and Distributed Computing 8, no. 5 (2015): 245-256.
  2. Masdari, Mohammad, Farbod Salehi, Marzie Jalali, and Moazam Bidaki. "A survey of PSO-based scheduling algorithms in cloud computing." Journal of Network and Systems Management 25, no. 1 (2017): 122-158.
  3. Lakra, Atul Vikas, and Dharmendra Kumar Yadav. "Multi-objective tasks scheduling algorithm for cloud computing throughput optimization." Procedia Computer Science 48 (2015): 107-113.
  4. Madni, Syed Hamid Hussain, Muhammad Shafie Abd Latiff, Mohammed Abdullahi, and Mohammed Joda Usman. "Performance comparison of heuristic algorithms for task scheduling in IaaS cloud computing environment." PloS one 12, no. 5 (2017): e0176321.
  5. Navimipour, Nima Jafari, and Farnaz Sharifi Milani. "Task scheduling in the cloud computing based on the cuckoo search algorithm." International Journal of Modeling and Optimization 5, no. 1 (2015): 44.
  6. Matos, Jocksam G. De, Carla K. De M. Marques, and Carlos HP Liberalino. "Genetic and static algorithm for task scheduling in cloud computing." International Journal of Cloud Computing 8, no. 1 (2019): 1-19.
  7. Panda, Sanjaya K., and Prasanta K. Jana. "An energy-efficient task scheduling algorithm for heterogeneous cloud computing systems." Cluster Computing 22, no. 2 (2019): 509-527.
  8. Arunarani, A. R., D. Manjula, and Vijayan Sugumaran. "Task scheduling techniques in cloud computing: A literature survey." Future Generation Computer Systems 91 (2019): 407-415.
  9. Gamal, Marwa, Rawya Rizk, Hani Mahdi, and Basem Elhady. "Bio-inspired Based Task Scheduling in Cloud Computing." In Machine Learning Paradigms: Theory and Application, pp. 289-308. Springer, Cham, 2019.
  10. Yiqiu, Fang, Xiao Xia, and Ge Junwei. "Cloud Computing Task Scheduling Algorithm Based On Improved Genetic Algorithm." In 2019 IEEE 3rd Information Technology, Networking, Electronic and Automation Control Conference (ITNEC), pp. 852-856. IEEE, 2019.
  11. Kashikolaei, Seyedeh Monireh Ggasemnezhad, Ali Asghar Rahmani Hosseinabadi, Behzad Saemi, Morteza Babazadeh Shareh, Arun Kumar Sangaiah, and Gui-Bin Bian. "An enhancement of task scheduling in cloud computing based on imperialist competitive algorithm and firefly algorithm." The Journal of Supercomputing (2019): 1-28.
  12. Wang, Qing, Xue-Liang Fu, Gai-Fang Dong, and Tao Li. "Research on cloud computing task scheduling algorithm based on particle swarm optimization." Journal of Computational Methods in Sciences and Engineering Preprint (2019): 1-9.
  13. Maguluri, Siva Theja, Rayadurgam Srikant, and Lei Ying. "Stochastic models of load balancing and scheduling in cloud computing clusters." In 2012 Proceedings IEEE Infocom, pp. 702-710. IEEE, 2012.
  14. Guo, Lizheng, Shuguang Zhao, Shigen Shen, and Changyuan Jiang. "Task scheduling optimization in cloud computing based on heuristic algorithm." Journal of networks 7, no. 3 (2012): 547.
  15. Zhang, Luna Mingyi, Keqin Li, and Yan-Qing Zhang. "Green task scheduling algorithms with speeds optimization on heterogeneous cloud servers." In Proceedings of the 2010 IEEE/ACM Int'l Conference on Green Computing and Communications & Int'l Conference on Cyber, Physical and Social Computing, pp. 76-80. IEEE Computer Society, 2010.
  16. Zhou, Zhou, Fangmin Li, Huaxi Zhu, Houliang Xie, Jemal H. Abawajy, and Morshed U. Chowdhury. "An improved genetic algorithm using greedy strategy toward task scheduling optimization in cloud environments." Neural Computing and Applications (2019): 1-11.
  17. Jana, Bappaditya, Moumita Chakraborty, and Tamoghna Mandal. "A task scheduling technique based on particle swarm optimization algorithm in cloud environment." In Soft Computing: Theories and Applications, pp. 525-536. Springer, Singapore, 2019.
  18. Abazari, Farzaneh, Morteza Analoui, Hassan Takabi, and Song Fu. "MOWS: multi-objective workflow scheduling in cloud computing based on heuristic algorithm." Simulation Modelling Practice and Theory 93 (2019): 119-132.
  19. Abdullahi, Mohammed, Md Asri Ngadi, Salihu Idi Dishing, and Barroon Isma'eel Ahmad. "An efficient symbiotic organisms search algorithm with chaotic optimization strategy for multi-objective task scheduling problems in cloud computing environment." Journal of Network and Computer Applications 133 (2019): 60-74.
  20. Geng, Xiaozhong, Lan Yu, Jie Bao, and Geji Fu. "A task scheduling algorithm based on priority list and task duplication in cloud computing environment." In Web Intelligence, vol. 17, no. 2, pp. 121-129. IOS Press, 2019.
  21. Panda, Sanjaya K., Indrajeet Gupta, and Prasanta K. Jana. "Task scheduling algorithms for multi-cloud systems: allocation-aware approach." Information Systems Frontiers 21, no. 2 (2019): 241-259.
  22. Li, Jian-Feng, and Jian Peng. "Task scheduling algorithm based on improved genetic algorithm in cloud computing environment." Jisuanji Yingyong/ Journal of Computer Applications 31, no. 1 (2011): 184-186.
  23. Salot, Pinal. "A survey of various scheduling algorithm in cloud computing environment." International Journal of Research in Engineering and Technology 2, no. 2 (2013): 131-135.