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Task scheduling algorithms for multi-cloud systems: allocation-aware approach

Author

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  • Sanjaya K. Panda

    (Veer Surendra Sai University of Technology)

  • Indrajeet Gupta

    (Indian Institute of Technology (ISM))

  • Prasanta K. Jana

    (Indian Institute of Technology (ISM))

Abstract

Cloud computing has gained enormous popularity for on-demand services on a pay-per-use basis. However, a single data center may be limited in providing such services, particularly in the peak demand time as it may not have unlimited resource capacity. Therefore, multi-cloud environment has been introduced in which multiple clouds can be integrated together to provide a unified service in a collaborative fashion. However, task scheduling in such environment is much more challenging than that is used in the single cloud environment. In this paper, we propose three allocation-aware task scheduling algorithms for a multi-cloud environment. The algorithms are based on the traditional Min-Min and Max-Min algorithm and extended for multi-cloud environment. All the algorithms undergo three common phases, namely matching, allocating and scheduling to fit them in the multi-cloud environment. We perform extensive simulations on the proposed algorithms and test with various benchmark and synthetic datasets. We evaluate the performance of the proposed algorithms in terms of makespan, average cloud utilization and throughput and compare the results with the existing algorithms in such system. The comparison results clearly demonstrate the efficacy of the proposed algorithms.

Suggested Citation

  • Sanjaya K. Panda & Indrajeet Gupta & Prasanta K. Jana, 2019. "Task scheduling algorithms for multi-cloud systems: allocation-aware approach," Information Systems Frontiers, Springer, vol. 21(2), pages 241-259, April.
    • Handle: RePEc:spr:infosf:v:21:y:2019:i:2:d:10.1007_s10796-017-9742-6
    DOI: 10.1007/s10796-017-9742-6
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    References listed on IDEAS

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    1. Jianxin Liao & Di Yang & Tonghong Li & Jingyu Wang & Qi Qi & Xiaomin Zhu, 2014. "A scalable approach for content based image retrieval in cloud datacenter," Information Systems Frontiers, Springer, vol. 16(1), pages 129-141, March.
    2. J. Octavio Gutierrez-Garcia & Kwang Mong Sim, 2012. "GA-based cloud resource estimation for agent-based execution of bag-of-tasks applications," Information Systems Frontiers, Springer, vol. 14(4), pages 925-951, September.
    3. Sanjaya K. Panda & Prasanta K. Jana, 0. "Normalization-Based Task Scheduling Algorithms for Heterogeneous Multi-Cloud Environment," Information Systems Frontiers, Springer, vol. 0, pages 1-27.
    4. JongBeom Lim & Taeweon Suh & JoonMin Gil & Heonchang Yu, 2014. "Scalable and leaderless Byzantine consensus in cloud computing environments," Information Systems Frontiers, Springer, vol. 16(1), pages 19-34, March.
    5. Kuan-Chou Lai & You-Fu Yu, 2012. "A scalable multi-attribute hybrid overlay for range queries on the cloud," Information Systems Frontiers, Springer, vol. 14(4), pages 895-908, September.
    6. Íñigo Goiri & Jordi Guitart & Jordi Torres, 2012. "Economic model of a Cloud provider operating in a federated Cloud," Information Systems Frontiers, Springer, vol. 14(4), pages 827-843, September.
    7. Mohammed Nassim Lacheheub & Ramdane Maamri, 2016. "Towards a construction of an intelligent business process based on cloud services and driven by degree of similarity and QoS," Information Systems Frontiers, Springer, vol. 18(6), pages 1085-1102, December.
    8. Seokho Son & Kwang Mong Sim, 2015. "Adaptive and similarity-based tradeoff algorithms in a price-timeslot-QoS negotiation system to establish cloud SLAs," Information Systems Frontiers, Springer, vol. 17(3), pages 565-589, June.
    9. Mohammad Mehedi Hassan & M. Shamim Hossain & A. M. Jehad Sarkar & Eui-Nam Huh, 2014. "Cooperative game-based distributed resource allocation in horizontal dynamic cloud federation platform," Information Systems Frontiers, Springer, vol. 16(4), pages 523-542, September.
    10. Gang Li & Mingchuan Wei, 2014. "Everything-as-a-service platform for on-demand virtual enterprises," Information Systems Frontiers, Springer, vol. 16(3), pages 435-452, July.
    11. Manoj Thomas & Daniela Costa & Tiago Oliveira, 2016. "Assessing the role of IT-enabled process virtualization on green IT adoption," Information Systems Frontiers, Springer, vol. 18(4), pages 693-710, August.
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