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A Cost-Effective Time-Constrained Multi-workflow Scheduling Strategy in Fog Computing

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Service-Oriented Computing – ICSOC 2018 Workshops (ICSOC 2018)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 11434))

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Abstract

With the rapid development of Internet of Things and smart services, massive intelligent devices are accessing the cloud data centers, which can cause serious network congestion and high latency issues. Recently, fog computing becomes a popular computing paradigm which can provide computing resources close to the end devices and solve various problems of existing cloud-only based systems. However, due to QoS (Quality of Service) constraints such as time and cost, and also the complexity of various resource types such as end devices, fog nodes and cloud servers, task scheduling in fog computing is still an open issue. To address such a problem, this paper presents a cost-effective scheduling strategy for multi-workflow with time constraints. Firstly, we define the models for workflow execution time and resource cost in fog computing. Afterwards, a novel PSO (Particle Swarm Optimization) based multi-workflow scheduling strategy is proposed where a fitness function is used to evaluate the workflow execution cost under given deadlines. A heart rate monitoring App is employed as a motivating example and comprehensive experimental results show that our proposed strategy can significantly reduce the execution cost of multiple workflows under given deadlines compared with other strategies.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China under No. 61672034, 61300042, and the Natural Science Foundation of Anhui Province of China under No. 1708085MF160, and the Key Natural Science Foundation of Education Bureau of Anhui Province Project No. KJ2018A0010.

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Authors and Affiliations

  1. School of Computer Science and Technology, Anhui University, Hefei, China

    Ruimiao Ding, Xuejun Li & Jia Xu

  2. School of Information Technology, Deakin University, Geelong, Australia

    Xiao Liu

Authors
  1. Ruimiao Ding
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  2. Xuejun Li
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  3. Xiao Liu
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  4. Jia Xu
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Corresponding author

Correspondence to Xuejun Li .

Editor information

Editors and Affiliations

  1. Deakin University, Melbourne, VIC, Australia

    Xiao Liu

  2. University of Pau and Pays, Pau Cedex, France

    Michael Mrissa

  3. Fudan University, Shanghai Shi, China

    Liang Zhang

  4. LIRIS Lab, University Lyon 1, IUT, Villeurbanne Cedex, France

    Djamal Benslimane

  5. School of IT and Computer Science, University of Wollongong, Wollongong, NSW, Australia

    Aditya Ghose

  6. Harbin Institute of Technology, Harbin, China

    Zhongjie Wang

  7. Scientific and Technological Hub, Fondazione Bruno Kessler (FBK), Trento, Italy

    Antonio Bucchiarone

  8. Macquarie University, Sydney, NSW, Australia

    Wei Zhang

  9. Queen’s University, Kingston, ON, Canada

    Ying Zou

  10. Rochester Institute of Technology, Rochester, NY, USA

    Qi Yu

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Ding, R., Li, X., Liu, X., Xu, J. (2019). A Cost-Effective Time-Constrained Multi-workflow Scheduling Strategy in Fog Computing. In: Liu, X., et al. Service-Oriented Computing – ICSOC 2018 Workshops. ICSOC 2018. Lecture Notes in Computer Science(), vol 11434. Springer, Cham. https://doi.org/10.1007/978-3-030-17642-6_17

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  • DOI: https://doi.org/10.1007/978-3-030-17642-6_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-17641-9

  • Online ISBN: 978-3-030-17642-6

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