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IJSTR >> Volume 9 - Issue 1, January 2020 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



A Survey On Task Scheduling Algorithms In Cloud Computing

[Full Text]

 

AUTHOR(S)

Namrata Bulchandani, Uday Chourasia, Shikha Agrawal, Priyanka Dixit, Alpana Pandey

 

KEYWORDS

Cloud computing, scheduling algorithms, Task scheduling.

 

ABSTRACT

Cloud Computing has gained immense importance in recent times. Cloud computing means delivering or utilizing services and resources over the internet. Task scheduling is very important aspect for maximum utilization of the cloud. Task scheduling in cloud computing is nothing but allotting different tasks to particular resources or machines such that the main purpose of moving to cloud is achieved i.e. high performance, maximum profit and minimum time. There can be more justifications to why ‘scheduling’ is ongoing hot research topic nowadays. Services are provided on pay-per-use basis. There are many scheduling algorithms proposed all having different target parameters. In this writing, different models of scheduling algorithms have been studied along with comparison and tabulation of latest proposed cloud scheduling algorithms.

 

REFERENCES

[1] M. Nir, A. Matrawy and M. St-Hilaire, "Economic and Energy Considerations for Resource Augmentation in Mobile Cloud Computing," in IEEE Transactions on Cloud Computing, vol. 6, no. 1, pp. 99-113, 1 Jan.-March 2018
[2] M. Nir, A. Matrawy and M. St-Hilaire, "An energy optimizing scheduler for mobile cloud computing environments," 2014 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), Toronto, ON, 2014, pp. 404-409
[3] W. Zhang and Y. Wen, "Energy-Efficient Task Execution for Application as a General Topology in Mobile Cloud Computing," in IEEE Transactions on Cloud Computing, vol. 6, no. 3, pp. 708-719, 1 July-Sept. 2018
[4] C. Chen, J. Lin and S. Kuo, "MapReduce Scheduling for Deadline-Constrained Jobs in Heterogeneous Cloud Computing Systems," in IEEE Transactions on Cloud Computing, vol. 6, no. 1, pp. 127-140, 1 Jan.-March 2018
[5] Y. Chen, G. Xie and R. Li, "Reducing Energy Consumption With Cost Budget Using Available Budget Preassignment in Heterogeneous Cloud Computing Systems," in IEEE Access, vol. 6, pp. 20572-20583, 2018.
[6] Liu, L., Fan, Q., & Buyya, R. (2018). A deadline-constrained multi-objective task scheduling algorithm in Mobile Cloud environments. IEEE Access
[7] Performance of integrated workload scheduling and pre-fetching in multimedia mobile cloud computing. Khorramnejad, K., Ferdouse, L., Guan, L. et al. J Cloud Comp (2018) 7: 13. https://doi.org/10.1186/s13677-018-0115-6
[8] Cost-Effective Algorithm for Workflow Scheduling in Cloud Computing Under Deadline Constraint Nasr, A.A., El-Bahnasawy, N.A., Attiya, G. et al. Arab J Sci Eng (2019) 44: 3765. https://doi.org/10.1007/s13369-018-3664-6

[9] Haque M., Islam R., Rubayeth Kabir M., Narin Nur F., Nessa Moon N. (2019) A Priority-Based Process Scheduling Algorithm in Cloud Computing. In: Abraham A., Dutta P., Mandal J., Bhattacharya A., Dutta S. (eds) Emerging Technologies in Data Mining and Information Security. Advances in Intelligent Systems and Computing, vol 755. Springer, Singapore
[10] Z. Wen, J. Cała, P. Watson and A. Romanovsky, "Cost Effective, Reliable and Secure Workflow Deployment over Federated Clouds," in IEEE Transactions on Services Computing, vol. 10, no. 6, pp. 929-941, 1 Nov.-Dec. 2017.
[11] A novel task scheduling scheme in a cloud computing environment using hybrid biogeography-based optimization. Tong, Z., Chen, H., Deng, X. et al. Soft Computing (2018). https://doi.org/10.1007/s00500-018-3657-0
[12] [12] Moon, Y., Yu, H., Gil, JM. et al. Hum. Cent. Comput. Inf. Sci. (2017) 7:28 https://doi.org/10.1186/s13673-017-0109-2 A slave ants based ant colony optimization algorithm for task scheduling in cloud computing environments.
[13] Kaur, S., Bagga, P., Hans, R. et al. Arab J Sci Eng (2019) 44: 2867. https://doi.org/10.1007/s13369-018-3614-3 Quality of Service (QoS) Aware Workflow Scheduling (WFS) in Cloud Computing
[14] de Souza, F.R., Miers, C.C., Fiorese, A. et al. J Grid Computing (2019). https://doi.org/10.1007/s10723-019-09479-x QVIA-SDN: Towards QoS-Aware Virtual Infrastructure Allocation on SDN-based Clouds. Journal of Grid Computing
[15] Chunlin, L., Jianhang, T. & Youlong, L. J Grid Computing (2019). https://doi.org/10.1007/s10723-019-09481-3 Hybrid Cloud Adaptive Scheduling Strategy for Heterogeneous Workloads. Journal of Grid Computing
[16] Juefu Liu and Gang Li, "An improved MIN-MIN grid tasks scheduling algorithm based on QoS constraints," 2010 International Conference on Optics, Photonics and Energy Engineering (OPEE), Wuhan, 2010, pp. 281-283
[17] He, X., Sun, X. & von Laszewski, G. J. Comput. Sci. & Technol. (2003) 18: 442. https://doi.org/10.1007/BF02948918 A QoS Guided Min-Min Heuristic for Grid Task Scheduling
[18] S. Song, Y. -. Kwok and K. Hwang, "Security-driven heuristics and a fast genetic algorithm for trusted grid job scheduling," 19th IEEE International Parallel and Distributed Processing Symposium, Denver, CO, 2005, pp. 10
[19] F. Ying and G. Lei, "Optimal Scheduling Simulation of Software for Multi-tenant in Cloud Computing Environment," 2014 Fifth International Conference on Intelligent Systems Design and Engineering Applications, Hunan, 2014, pp. 688-692
[20] Y. Vijay and B. V. Ghita, "Evaluating cloud computing scheduling algorithms under different environment and scenarios," 2017 8th International Conference on Computing, Communication and Networking Technologies (ICCCNT), Delhi, 2017, pp. 1-5
[21] Y. K. Yu-Kwong Kwok and I. Ahmad, "A Static Scheduling Algorithm Using Dynamic Critical Path for Assigning Parallel Algorithms onto Multiprocessors," 1994 Internatonal Conference on Parallel Processing Vol. 2, North Carolina, USA, 1994, pp. 155-159
[22] HCOC: a cost optimization algorithm for workflow scheduling in hybrid clouds. Journal of Internet Services and Applications, 2011, Volume 2, Number 3, Page 207
[23] H. Chen, X. Zhu, G. Liu and W. Pedrycz, "Uncertainty-Aware Online Scheduling for Real-Time Workflows in Cloud Service Environment," in IEEE Transactions on Services Computing