Skip to main content
SpringerLink
Log in

Real-Time Task Scheduling and Dynamic Resource Allocation in Fog Infrastructure

  • Conference paper
  • First Online:
Advanced Information Networking and Applications (AINA 2024)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 200))

  • 177 Accesses

Abstract

Efficient task scheduling in Fog Computing infrastructures necessitates adaptive solutions to dynamically manage real-time tasks and improve the utilization of resources. In this paper, we propose a real-time dynamic task scheduler that assigns incoming tasks to fog nodes based on maximizing resource utilization and satisfying task deadlines. The proposed approach leverages optimization technique and heuristic algorithm to allocate fog resources and schedule real-time tasks efficiently. The objective is an efficient use of resources while ensuring tasks are executed within their specified deadlines. Hence, the algorithm aims to maximize resource utilization in the architecture so that a large percentage of real-time tasks meet their deadline. The algorithm is implemented in the iFogSim simulator, and its performances are evaluated and compared to other algorithms.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 249.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Salimi, R., Azizi, S. Abawajy, J.: A greedy randomized adaptive search procedure for scheduling IoT tasks in virtualized fog-cloud computing (2023)

    Google Scholar 

  2. Sultan Hajam, S.: Deadline-cost aware task scheduling algorithm in fog computing networks. Int. J. Commun. Syst. 37, e5695 (2024)

    Article  Google Scholar 

  3. Azizi, S., Shojafar, M., Abawajy, J., Buyya, R.: Deadline-aware and energy-efficient IoT task scheduling in fog computing systems: a semi-greedy approach. J. Netw. Comput. Appl. 201, 103333 (2022)

    Article  Google Scholar 

  4. Ali, H., Rout, R., Parimi, P., Das, S.: Real-time task scheduling in fog-cloud computing framework for iot applications: a fuzzy logic based approach. In: 2021 International Conference On COMmunication Systems & NETworkS (COMSNETS), pp. 556–564 (2021)

    Google Scholar 

  5. Bonomi, F., Milito, R., Zhu, J. Addepalli, S.: Fog computing and its role in the internet of things. In: Proceedings of the First Edition of the MCC Workshop on Mobile Cloud Computing, pp. 13–16 (2012)

    Google Scholar 

  6. Jamil, B., Ijaz, H., Shojafar, M., Munir, K., Buyya, R.: Resource allocation and task scheduling in fog computing and internet of everything environments: a taxonomy, review, and future directions. ACM Comput. Surv. (CSUR) 54, 1–38 (2022)

    Article  Google Scholar 

  7. Yin, L., Luo, J., Luo, H.: Tasks scheduling and resource allocation in fog computing based on containers for smart manufacturing. IEEE Trans. Ind. Inform. 14, 4712–4721 (2018)

    Article  Google Scholar 

  8. Gupta, H., Vahid Dastjerdi, A., Ghosh, S., Buyya, R.: iFogSim: a toolkit for modeling and simulation of resource management techniques in the Internet of Things, Edge and Fog computing environments. Softw. Pract. Exper. 47, 1275–1296 (2017)

    Google Scholar 

  9. Sharif, Z., Jung, L., Ayaz, M., Yahya, M., Pitafi, S.: Priority-based task scheduling and resource allocation in edge computing for health monitoring system. J. King Saud Univ.-Comput. Inf. Sci. 35, 544–559 (2023)

    Google Scholar 

  10. Choudhari, T., Moh, M., Moh, T.: Prioritized task scheduling in fog computing. In: Proceedings Of The ACMSE 2018 Conference, pp. 1–8 (2018)

    Google Scholar 

  11. Jamil, B., Ijaz, H., Shojafar, M., Munir, K.: IRATS: a DRL-based intelligent priority and deadline-aware online resource allocation and task scheduling algorithm in a vehicular fog network. Ad Hoc Netw. 141, 103090 (2023)

    Article  Google Scholar 

  12. Stavrinides, G., Karatza, H.: A hybrid approach to scheduling real-time IoT workflows in fog and cloud environments. Multimedia Tools Appl. 78, 24639–24655 (2019)

    Article  Google Scholar 

  13. Sharma, O., Rathee, G., Kerrache, C., Herrera-Tapia, J.: Two-stage optimal task scheduling for smart home environment using fog computing infrastructures. Appl. Sci. 13, 2939 (2023)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Faculty of Sciences of Tunis, University of Tunis El Manar, Tunis, Tunisia

    Mayssa Trabelsi & Samir Ben Ahmed

Authors
  1. Mayssa Trabelsi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Samir Ben Ahmed
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mayssa Trabelsi .

Editor information

Editors and Affiliations

  1. Department of Information and Communication Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

Rights and permissions

Reprints and permissions

Copyright information

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

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Trabelsi, M., Ben Ahmed, S. (2024). Real-Time Task Scheduling and Dynamic Resource Allocation in Fog Infrastructure. In: Barolli, L. (eds) Advanced Information Networking and Applications. AINA 2024. Lecture Notes on Data Engineering and Communications Technologies, vol 200. Springer, Cham. https://doi.org/10.1007/978-3-031-57853-3_33

Download citation

Publish with us

Policies and ethics

Search

Navigation