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Cost-Deadline Constrained Robust Scheduling of Workflows Using Hybrid Instances in IaaS Cloud

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Artificial Intelligence of Things (ICAIoT 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1929))

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Abstract

Cloud Computing has gained popularity due to the on-demand resource allocation in the distributed computing environments and provides resources that are dynamically scalable on the “pay as you go” model. Over the past years, Amazon has started providing a new service called EC2 Spot Instances which provides their idle machines on rent in the spot market at a lower cost. Spot instances are the unused virtual machines which are accessible at almost 75% lower price than their on-demand price to perform compute-intensive tasks. Spot instances will end up till the current spot price is less than the user’s bid price. In this paper for the cloud environment, the IaaS Cloud Partial Critical Paths(IC-PCP) algorithm is expanded with the aim of reducing execution costs while still meeting user-defined deadlines. ICPCP schedules the task by finding a computation service which can execute complete critical path before its latest finish time. The work presented in this paper proposes a workflow scheduling algorithm, IaaS Cloud Partial Critical Paths with robustness(IC-PCPR) uses both on-demand and spot instances to reduce the cost of workflow execution while satisfying a user-defined deadline and making system robust that runs on heterogeneous resources. The proposed work is simulated in MATLAB framework and the experimental results based on three scientific workflows show that the ICPCPR performs much better than ICPCP algorithm.

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References

  1. Zhang, Q., Cheng, L., Boutaba, R.: Cloud computing: State-of-the-art and research challenges. J. Internet Serv. Appl. 1, 7–18 (2010). https://doi.org/10.1007/s13174-010-0007-6

    Article  Google Scholar 

  2. Amin, Z., Sethi, N., Singh, H.: Review on fault tolerance techniques in cloud computing. Int. J. Comput. Appl.Comput. Appl. 116, 11–17 (2015). https://doi.org/10.5120/20435-2768

    Article  Google Scholar 

  3. Keshk, A.E., El-Sisi, A.B., Tawfeek, M.A.: Cloud task scheduling for load balancing based on intelligent strategy. Int. J. Intell. Syst. Appl. 6, 25–36 (2014). https://doi.org/10.5815/ijisa.2014.05.02

  4. Mei, J., Li, K., Zhou, X., Li, K.: Fault-tolerant dynamic rescheduling for heterogeneous computing systems. J. Grid Comput. 13, 507–525 (2015). https://doi.org/10.1007/s10723-015-9331-1

    Article  Google Scholar 

  5. Chandrashekar, D.P.: Robust and fault-tolerant scheduling for scientific workflows in cloud computing environments. In: IEEE 28th International Conference on Advanced Information Networking and Applications, pp. 858–865 (2015)

    Google Scholar 

  6. Bala, A., Chana, I.: Fault tolerance- challenges, techniques and implementation in cloud computing. Int. J. Comput. Sci. Softw. Issues. 9, 288–293 (2012)

    Google Scholar 

  7. Bala, A., Chana, I.: Autonomic fault tolerant scheduling approach for scientific workflows in Cloud computing. Concurr. Eng. Res. Appl. 23, 27–39 (2015). https://doi.org/10.1177/1063293X14567783

    Article  Google Scholar 

  8. Poola, D., Ramamohanarao, K., Buyya, R.: Enhancing reliability of workflow Execution using task replication. ACM Trans. Auton. Adapt. Syst. 10 (2016)

    Google Scholar 

  9. Introduction, A., Instances, S.: Amazon Elastic Compute Cloud An Introduction to Spot Instances. (2011)

    Google Scholar 

  10. Abrishami, S., Naghibzadeh, M., Epema, D.H.J.: Deadline-constrained workflow scheduling algorithms for infrastructure as a service clouds. Futur. Gener. Comput. Syst.. Gener. Comput. Syst. 29, 158–169 (2013). https://doi.org/10.1016/j.future.2012.05.004

    Article  Google Scholar 

  11. Voorsluys, W., Buyya, R.: Reliable provisioning of spot instances for compute-intensive applications. In: Proceedings of IEEE 26th  International Conference on Advanced Information Networking and Applications, pp. 542–549 (2011)

    Google Scholar 

  12. Farid, M., Latip, R., Hussin, M., Hamid, N.A.W.A.: A fault-intrusion-tolerant system and deadline-aware algorithm for scheduling scientific workflow in the cloud. PeerJ Comput. Sci. 7, 1–21 (2021). https://doi.org/10.7717/PEERJ-CS.747

    Article  Google Scholar 

  13. Liu, W., Wang, P., Meng, Y., Zhao, C., Zhang, Z.: Cloud spot instance price prediction using kNN regression. https://doi.org/10.1186/s13673-020-00239-5

  14. Wang, P., Zhao, C., Zhang, Z.: An ant colony algorithm-based approach for cost-effective data hosting with high availability in multi-cloud environments. In: ICNSC 2018 - 15th IEEE International Conference on Networking, Sensing and Control, pp.1–6 (2018). https://doi.org/10.1109/ICNSC.2018.8361288

  15. Yi, S., Kondo, D., Andrzejak, A.: Reducing costs of spot instances via checkpointing in the Amazon elastic compute cloud. In: Proceedings of IEEE 3rd International Conference of Cloud Computing, CLOUD, pp. 236–243 (2010). https://doi.org/10.1109/CLOUD.2010.35

  16. Poola, D., Ramamohanarao, K., Buyya, R.: Fault-Tolerant workflow scheduling using spot instances on clouds. Procedia Comput. Sci. 29, 523–533 (2014). https://doi.org/10.1016/j.procs.2014.05.047

    Article  Google Scholar 

  17. Bharathi, S., Chervenak, A., Deelman, E., Mehta, G., Su, M.H., Vahi, K.: Characterization of scientific workflows. Work. Support Large-Scale Sci. Work (2017). https://doi.org/10.1109/WORKS.2008.4723958

  18. Ma, X., Gao, H., Xu, H., Bian, M.: An IoT-based task scheduling optimization scheme considering the deadline and cost- aware scientific workflow for cloud computing. EURASIP J. Wirel. Commun. Netw. (2019). https://doi.org/10.1186/s13638-019-1557-3

  19. Amazon EC2 On-Demand Pricing, https://aws.amazon.com/ec2/pricing/on-demand/ (last visited on August 2017)

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Authors and Affiliations

  1. CSIR-Central Scientific Instruments Organisation (CSIO), Chandigarh, India

    Urvashi Nag & Amrendra Sharan

  2. National Institute of Technical Teachers Training and Research, Chandigarh, India

    Mala Kalra

Authors
  1. Urvashi Nag
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  2. Amrendra Sharan
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  3. Mala Kalra
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Corresponding author

Correspondence to Urvashi Nag .

Editor information

Editors and Affiliations

  1. National Institute of Technical Teachers Training and Research, Chandigarh, India

    Rama Krishna Challa

  2. Durham University, Durham, UK

    Gagangeet Singh Aujla

  3. National Institute of Technical Teachers Training and Research, Chandigarh, India

    Lini Mathew

  4. National Institute of Technical Teachers Training and Research, Chandigarh, India

    Amod Kumar

  5. National Institute of Technical Teachers Training and Research, Chandigarh, India

    Mala Kalra

  6. National Institute of Technical Teachers Training and Research, Chandigarh, India

    S. L. Shimi

  7. National Institute of Technical Teachers Training and Research, Chandigarh, India

    Garima Saini

  8. National Institute of Technical Teachers Training and Research, Chandigarh, India

    Kanika Sharma

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© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Nag, U., Sharan, A., Kalra, M. (2024). Cost-Deadline Constrained Robust Scheduling of Workflows Using Hybrid Instances in IaaS Cloud. In: Challa, R.K., et al. Artificial Intelligence of Things. ICAIoT 2023. Communications in Computer and Information Science, vol 1929. Springer, Cham. https://doi.org/10.1007/978-3-031-48774-3_16

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  • DOI: https://doi.org/10.1007/978-3-031-48774-3_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-48773-6

  • Online ISBN: 978-3-031-48774-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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