Abstract
Cloud computing has become the most attractive platform compared to grid computing, that offers several services such as infrastructure as a service, platform as a service, and software as a service, where the users can consume these services on the cloud and pay based on their consumption and on the fulfilment of Quality of Service (QoS) constraints such as deadline and budget. Hence, to schedule the tasks effectively, cost monetary must be considered while optimising implementation time performance under users’ defined constraints. In this paper, the Deadline Budget Scheduling (DBS) model is proposed to execute the users’ tasks on Virtual Machines (VMs) under the QoS constraints at less execution time. In our proposal, users’ tasks will be assigned to appropriate VM which meets either of the two constraints namely (deadline and budget) or one of the constraints based on user satisfaction. Makespan and cost are calculated to evaluate our proposed DBS model with state of the art algorithms. The experimental results illustrate that DBS outperforms other algorithms by minimizing the makespan and cost.
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.References
Panda, S.K., Gupta, I., Jana, P.K.: Task scheduling algorithms for multi-cloud systems: allocation-aware approach. Springer Science+Business Media, New York (2017)
Karthiban, K., Smys, S. Privacy preserving approaches in cloud computing. In: 2018 2nd International Conference on Inventive Systems and Control (ICISC). IEEE (2018)
Gill, S.S., et al.: BULLET: particle swarm optimization based scheduling technique for provisioned cloud resources. J. Netw. Syst. Manag. 26, 1–40 (2018)
Kalra, M., Singh, S.: A review of metaheuristic scheduling techniques in cloud computing. Egypt. Inf. J. 16(3), 275–295 (2015)
Tang, X., Li, X., Fu, Z.: Budget-constraint stochastic task scheduling on heterogeneous cloud systems. Concurr. Comput. Pract. Exp. 29(19), e4210 (2017)
Arabnejad, H., Barbosa, J.G.: List scheduling algorithm for heterogeneous systems by an optimistic cost table. IEEE Trans. Parallel Distrib. Syst. 25(3), 682–694 (2014)
Praveena, A., Smys, S. Ensuring data security in cloud based social networks. In: 2017 International Conference of Electronics, Communication and Aerospace Technology (ICECA). Vol. 2. IEEE (2017)
Panda, S.K., Jana, P.K.: SLA-based task scheduling algorithms for heterogeneous multi-cloud environment. J. Supercomput. 73(6), 2730–2762 (2017)
Arabnejad, H., Barbosa, J.G.: A budget constrained scheduling algorithm for workflow applications. J. Grid Comput. 12(4), 665–679 (2014)
Mao, Y., Zhong, H., Li, X. Hierarchical model-based associate tasks scheduling with the deadline constraints in the cloud. In: Proceeding of the 2015 IEEE International Conference on Information and Automation, Lijiang, China (2015)
Arabnejad, H., Barbosa, J.G. Budget constrained scheduling strategies for on-line workflow applications. In: International Conference on Computational Science and Its Applications. Springer, Cham (2014)
Deldari, A., Naghibzadeh, M., Abrishami, S.: CCA: a deadline-constrained workflow scheduling algorithm for multicore resources on the cloud. J. Supercomput. 73(2), 756–781 (2017)
Peng, Z., et al. A reinforcement learning-based mixed job scheduler scheme for cloud computing under SLA constraint. In: IEEE 3rd International Conference on Cyber Security and Cloud Computing (CSCloud), 2016. IEEE (2016)
Pop, F., Dobre, C., Cristea, V., Bessis, N., Xhafa, F., Barolli, L.: Deadline scheduling for aperiodic tasks in inter-cloud environments: a new approach to resource management. J. Supercomput 71, 1754–1765 (2015). https://doi.org/10.1007/s11227-014-1285-82015
Shin, S.M., Kim, Y., Lee, S.K. Deadline-guaranteed scheduling algorithm with improved resource utilization for cloud computing. In: 12th Annual IEEE Consumer Communications and Networking Conference (CCNC) (2015)
Alworafi, M.A., et al.: Cost-aware task scheduling in cloud computing environment. Int. J. Comput. Netw. Inf. Secur. 9(5), 52 (2017)
Thanasias, V., Lee, C., Hanif, M., Kim, E., Helal, S. VM capacity-aware scheduling within budget constraints in IaaS clouds. PLOS ONE https://doi.org/10.1371/journal.pone.0160456 (2016)
Chen, W., Xie, G., Li, R., Bai, Y., Fana, C., Li, K.: Efficient task scheduling for budget constrained parallel applications on heterogeneous cloud computing systems. Future Gener. Comput. Syst. 74, 1–11 (2017)
Rodriguez, M.A., Buyya, R. Budget-driven scheduling of scientific workflows in IaaS clouds with fine-grained billing periods. ACM Trans. Auton. Adapt. Syst. 12(2). doi: http://dx.doi.org/10.1145/3041036 (2017)
Saxena, D., Dr, R.K., Chauhan, D., Kait, R.: Dynamic fair priority optimization task scheduling algorithm in cloud computing: concepts and implementations. I J Comput. Netw. Inf. Secur. 2, 41–48 (2016)
Arabnejad, H., Barbosa, J.G., Prodan, R.: Low-time complexity budget–deadline constrained workflow scheduling on heterogeneous resources. Future Gener. Comput. Syst. 55, 29–40 (2016)
Khorsand, R., Safi-Esfahani, F., Nematbakhsh, N., Mohsenzade, M.: ATSDS: adaptive two-stage deadline-constrained workflow scheduling considering run-time circumstances in cloud computing environments. J. Supercomput. 73(6), 2430–2455 (2016)
Arabnejad, H., Barbosa, J.G.: Multi-QoS constrained and Profit-aware scheduling approach for concurrent workflows on heterogeneous systems. Future Gener. Comput. Syst. 68, 211–221 (2017)
Verma, A., Kaushal, S.: A hybrid multi-objective particle swarm optimization for scientific workflow scheduling. Parallel Comput. 62, 1–19 (2017)
Alworafi, M.A., et al. An improved SJF scheduling algorithm in cloud computing environment. In: International Conference on Electrical, Electronics, Communication, Computer and Optimization Techniques (ICEECCOT), IEEE (2016)
Dhari, A., Arif, K.I.: An efficient load balancing scheme for cloud computing. Indian J. Sci. Technol. 10(11), 1–8 (2017)
Alworafi, M.A., Mallappa, S.: An enhanced task scheduling in cloud computing based on deadline-aware model. Int. J. Grid High Perform. Comput. 10(1), 31–53 (2018)
Nawaz, S. Real Time Tasks Scheduling in Cloud Computing Environment. Diss. National Institute of Technology Rourkela (2015)
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Alworafi, M.A., Mallappa, S. A collaboration of deadline and budget constraints for task scheduling in cloud computing. Cluster Comput 23, 1073–1083 (2020). https://doi.org/10.1007/s10586-019-02978-2
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10586-019-02978-2