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Scheduling Method Based on Backfill Strategy for Multiple DAGs in Cloud Computing

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Data Science (ICPCSEE 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1059))

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Abstract

Multiple DAGs scheduling strategy is a critical factor affecting resource utilization and operating cost in the cloud computing. To solve the problem that multiple DAG scheduling cannot meet the resource utilization and reliability when multiple DAGs arrive at different time, the multiple DAGs scheduling problem can be transformed into a single DAG scheduling problem with limited resource available time period through multiple DAGs scheduling model based on backfill. On the basis of discussing the available time period description of resources and the sorting of task scheduling when the available time period is limited, the multiple DAGs scheduling strategy is proposed based on backfill. The experimental analysis shows that this strategy can effectively shorten the makespan and improve the resources utilization when multiple DAGs arrive at different time.

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References

  1. Jia-Xin, Y., et al.: Time-aware minimum area task scheduling algorithm based on backfilling algorithm. Comput. Sci. 45(8), 100–104 (2018)

    Google Scholar 

  2. Huang-Ke, C., et al.: Cost-efficient reactive scheduling for real-time workflows in clouds. J. Supercomput. 74(11), 6291–6309 (2018)

    Article  Google Scholar 

  3. Jiang, X., Xiang, L.: Improved decomposition-based global EDF scheduling of DAGs. J. Circ. Syst. Comput. 27(7), 1–23 (2018)

    Article  Google Scholar 

  4. He-Jhan, J., et al.: Scheduling concurrent workflows in HPC cloud through exploiting schedule gaps. Algorithms Archit. Parallel Process. 7016, 283–293 (2011)

    Google Scholar 

  5. Bittencourt, L.F., Madeira, E.R.M.: HCOC: a cost optimization algorithm for workflow scheduling in hybrid clouds. J. Internet Serv. Appl. 2(3), 207–227 (2011)

    Article  Google Scholar 

  6. Javadi, B., Tomko, M., Sinnott, R.O.: Decentralized orchestration of data-centric workflows in cloud environments. Future Gener. Comput. Syst. 29(7), 1826–1837 (2013)

    Article  Google Scholar 

  7. Casanova, F., Suter, F.: On cluster resource allocation for multiple parallel task graphs. J. Parallel Distrib. Comput. 70(12), 1193–1203 (2010)

    Article  Google Scholar 

  8. Jia-Yu, Z., Dan, X.: Path priority-based heuristic task scheduling algorithm for cloud computing. Comput. Eng. Des. 34(10), 3511–3515 (2013)

    Google Scholar 

  9. Kan-Kan, L.: High performance algorithm for task scheduling in heterogeneous environment. Comput. Syst. Appl. 19(11), 102–105 (2010)

    Google Scholar 

  10. Ya-Qiu, L., Hong-Run, S., Wei-Peng, J.: DAG task scheduling integrating with security and availability in cloud environment. Comput. Eng. 40(12), 12–18 (2014)

    Google Scholar 

  11. Tian-Mei-Zi, C., Heng-Zhou, Y., Zhi-Dan, H.: k-HEFT: a static task scheduling algorithm in clouds. In: Proceedings of the 3rd International Conference on Intelligent Information Processing, ICIIP 2018, pp. 152–159 (2018)

    Google Scholar 

  12. Guo-Zhong, T., Chuang-Bai, X., Zhu-Sheng, X.: Hybrid scheduling strategy for multiple DAGs workflow in heterogeneous system. J. Softw. 23(10), 2720–2734 (2012)

    Article  Google Scholar 

  13. Yuan-Xiong, G., Yu-Guang, F.: Electricity cost saving strategy in data centers by using energy storage. IEEE Trans. Parallel Distrib. Syst 24(6), 1149–1160 (2013)

    Article  Google Scholar 

  14. Yue, S., Jiong, Y., Jian-Bo, Z.: Preemptive scheduling for multiple DAGs in cloud computing. Comput. Sci. 41(3), 145–148 (2014)

    Google Scholar 

  15. Jun, Z., et al.: Efficient fault-toleran scheduling on multiprocessor systems via replication and deallocation. Int. J. Embedded Syst. 6(2–3), 216–224 (2014)

    Google Scholar 

  16. Wei-Peng, J., et al.: Multiple DAGs dynamic workflow reliability scheduling algorithm in a cloud computing system. J. Xidian Univ. 43(2), 92–97 (2016)

    Google Scholar 

  17. Ji, L., Long-Hua, F., Sheng-Long, F.: An greedy-based job scheduling algorithm in cloud computing. J. Softw. 9(4), 921–925 (2014)

    Google Scholar 

  18. Topcuoglu, H., Hariri, S., Wu, M.Y.: Performance-effective and low-complexity task scheduling for heterogeneous computing. IEEE Trans. Parallel Distrib. Syst. 13(3), 260–274 (2002)

    Article  Google Scholar 

  19. Zhao, H., Sakellariou, R.: Scheduling multiple DAGs onto heterogeneous systems. In: Proceedings of the 20th International Conference on Parallel and Distributed Processing, IPDPS 2006 (2006)

    Google Scholar 

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Acknowledgment

This work is supported by Guangxi Universities key Laboratory Director Fund of Embedded Technology and Intelligent Information Processing (Guilin University of Technology) under Grand No. 2018A-05.

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Authors and Affiliations

  1. Guangxi Key Laboratory of Embedded Technology and Intelligent System, Guilin University of Technology, Guilin, 541006, China

    Zhidan Hu, Hengzhou Ye & Tianmeizi Cao

Authors
  1. Zhidan Hu
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  2. Hengzhou Ye
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  3. Tianmeizi Cao
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Corresponding author

Correspondence to Zhidan Hu .

Editor information

Editors and Affiliations

  1. College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China

    Rui Mao

  2. Harbin Institute of Technology, Harbin, China

    Hongzhi Wang

  3. Guilin University of Technology, Guilin, China

    Xiaolan Xie

  4. National Academy of Guo Ding Institute of Data Science, Harbin, China

    Zeguang Lu

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© 2019 Springer Nature Singapore Pte Ltd.

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Hu, Z., Ye, H., Cao, T. (2019). Scheduling Method Based on Backfill Strategy for Multiple DAGs in Cloud Computing. In: Mao, R., Wang, H., Xie, X., Lu, Z. (eds) Data Science. ICPCSEE 2019. Communications in Computer and Information Science, vol 1059. Springer, Singapore. https://doi.org/10.1007/978-981-15-0121-0_21

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  • DOI: https://doi.org/10.1007/978-981-15-0121-0_21

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-0120-3

  • Online ISBN: 978-981-15-0121-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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