Skip to main content

Advertisement

Springer Nature Link
Log in

An energy, delay and priority-aware task offloading algorithm for fog computing incorporating load balancing

  • Published:
The Journal of Supercomputing Aims and scope Submit manuscript

Abstract

Internet of things (IoT) and fog and cloud computing are the most widespread technologies that have become a part of our day-to-day activities. The integration of these technologies will become crucial components for the future of the Internet as their usage and acceptance rapidly increase. IoT devices (or terminal nodes (TNs)) have limited resource capability to carry out their generated tasks. Therefore, they depend on the cloud to assist them in completing all their tasks. However, the distance between TNs and the cloud may lead to network congestion and uneven delay. As a result, fog nodes (FNs) work as an intermediary between TNs and the cloud to minimize delay in completing the TNs’ tasks. In this context, previous studies assign the TNs’ tasks to FNs based on various criteria, namely energy, delay and priority among the tasks, without combining them. Fair task offloading (FTO) recently combines these criteria to assign the TN's tasks to FNs without significantly considering load balancing among FNs. This paper introduces a multi-objective task offloading algorithm called energy, delay and priority-aware task offloading (EDP-TO) by considering all the criteria and load balancing. The proposed algorithm uses the multi-objective function to select the FNs for offloading. It divides the tasks into multiple subtasks and assigns them to the chosen FNs, minimizing the overall delay. The performance of the proposed algorithm is shown without and with load balancing, called EDP-TO-WLB and EDP-TO-LB, and it is compared with FTO by considering three scenarios and five performance metrics. The comparison results show the EDP-TO improves a maximum of 3% energy, 5% delay and 45% fairness over the FTO.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Algorithm 1
Procedure 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16

Similar content being viewed by others

Availability of data and materials

The datasets can be provided on demand.

References

  1. Gubbi Jayavardhana, Buyya Rajkumar, Marusic Slaven, Palaniswami Marimuthu (2013) Internet of things (iot): a vision, architectural elements, and future directions. Futur Gener Comput Syst 29(7):1645–1660

    Article  Google Scholar 

  2. Ge Xiaohu, Yang Jing, Gharavi Hamid, Sun Yang (2017) Energy efficiency challenges of 5g small cell networks. IEEE Commun Mag 55(5):184–191

    Article  Google Scholar 

  3. Doshi Krupa B, Hyun Moon Seong, Whitaker Michael D, Lockhart Thurmon E (2023) Assessment of gait and posture characteristics using a smartphone wearable system for persons with osteoporosis with and without falls. Sci Rep 13(1):538

    Article  Google Scholar 

  4. Neha Benazir, Panda Sanjaya Kumar, Sahu Pradip Kumar, Sahoo Kshira Sagar, Gandomi Amir H (2022) A systematic review on osmotic computing. ACM Trans Internet Things 3(2):1–30

    Article  Google Scholar 

  5. Deng Yiqin, Chen Zhigang, Zhang Deyu, Zhao Ming (2018) Workload scheduling toward worst-case delay and optimal utility for single-hop fog-iot architecture. IET Commun 12(17):2164–2173

    Article  Google Scholar 

  6. Panda Sanjaya K, Jana Prasanta K (2015) Efficient task scheduling algorithms for heterogeneous multi-cloud environment. J Supercomput 71:1505–1533

    Article  Google Scholar 

  7. Buyya Rajkumar, Yeo Chee Shin, Venugopal Srikumar, Broberg James, Brandic Ivona (2009) Cloud computing and emerging it platforms: Vision, hype, and reality for delivering computing as the 5th utility. Futur Gener Comput Syst 25(6):599–616

    Article  Google Scholar 

  8. Panda Sanjaya K, Jana Prasanta K (2015) A multi-objective task scheduling algorithm for heterogeneous multi-cloud environment. In: 2015 International Conference on Electronic Design, Computer Networks & Automated Verification (EDCAV). IEEE, pp 82–87

  9. Panda Sanjaya K, Jana Prasanta K (2019) An energy-efficient task scheduling algorithm for heterogeneous cloud computing systems. Clust Comput 22(2):509–527

    Article  Google Scholar 

  10. Kwak Jeongho, Kim Yeongjin, Lee Joohyun, Chong Song (2015) Dream: dynamic resource and task allocation for energy minimization in mobile cloud systems. IEEE J Sel Areas Commun 33(12):2510–2523

    Article  Google Scholar 

  11. Panda Sanjaya K, Jana Prasanta K (2017) Sla-based task scheduling algorithms for heterogeneous multi-cloud environment. J Supercomput 73:2730–2762

    Article  Google Scholar 

  12. Botta Alessio, De Donato Walter, Persico Valerio, Pescape Antonio (2016) Integration of cloud computing and internet of things: a survey. Futur Gener Comput Syst 56:684–700

    Article  Google Scholar 

  13. Chiang Mung, Ha Sangtae, Risso Fulvio, Zhang Tao, Chih-Lin I (2017) Clarifying fog computing and networking: 10 questions and answers. IEEE Commun Mag 55(4):18–20

    Article  Google Scholar 

  14. Asif Thanedar Md, Kumar Panda Sanjaya (2023) A dynamic resource management algorithm for maximizing service capability in fog-empowered vehicular ad-hoc networks. Peer Peer NetwAppl 16(2):932–946

    Article  Google Scholar 

  15. Costa B, Bachiega J Jr, De Carvalho LR, Araujo AP (2022) Orchestration in fog computing: a comprehensive survey. ACM Comput Surv(CSUR) 55(2):1–34

    Google Scholar 

  16. Mostafa Haghi Kashani and Ebrahim Mahdipour (2023) Load balancing algorithms in fog computing. IEEE Trans Serv Comput 16(2):1505–1521

    Article  Google Scholar 

  17. Benazir Neha, Kumar Panda Sanjaya, Kumar Sahu Pradip, David Taniar (2024) Energy and latency-balanced osmotic-offloading algorithm for healthcare systems. Internet Things 26:101176

    Article  Google Scholar 

  18. Saini Kanika, Kalra Sheetal, Sood Sandeep K (2022) An integrated framework for smart earthquake prediction: iot, fog, and cloud computing. J Grid Comput 20(2):17

    Article  Google Scholar 

  19. Rajagopal Shinu M, Supriya M, Rajkumar Buyya (2023) Fedsdm: federated learning based smart decision making module for ecg data in iot integrated edge-fog-cloud computing environments. Internet Things 22:100784

    Article  Google Scholar 

  20. Zhang Guowei, Shen Fei, Liu Zening, Yang Yang, Wang Kunlun, Zhou Ming-Tuo (2018) Femto: fair and energy-minimized task offloading for fog-enabled iot networks. IEEE Internet Things J 6(3):4388–4400

    Article  Google Scholar 

  21. Chen Xu, Jiao Lei, Li Wenzhong, Xiaoming Fu (2015) Efficient multi-user computation offloading for mobile-edge cloud computing. IEEE/ACM Trans Netw 24(5):2795–2808

    Article  Google Scholar 

  22. Zhang Guowei, Shen Fei, Yang Yang, Qian Hua, Yao Wei (2018) Fair task offloading among fog nodes in fog computing networks. In 2018 IEEE International Conference on Communications (ICC). IEEE, pp 1–6

  23. Meng Xianling, Wang Wei, Zhang Zhaoyang (2017) Delay-constrained hybrid computation offloading with cloud and fog computing. IEEE Access 5:21355–21367

    Article  Google Scholar 

  24. Baccarelli Enzo, Vinueza Paola G, Naranjo Michele Scarpiniti, Shojafar Mohammad, Abawajy Jemal H (2017) Fog of everything: energy-efficient networked computing architectures, research challenges, and a case study. IEEE Access 5:9882–9910

    Article  Google Scholar 

  25. Asif Thanedar Md, Kumar Panda Sanjaya (2024) Energy and priority-aware scheduling algorithm for handling delay-sensitive tasks in fog-enabled vehicular networks. J Supercomput 80:1–23

    Google Scholar 

  26. Adhikari Mainak, Mukherjee Mithun, Srirama Satish Narayana (2019) Dpto: a deadline and priority-aware task offloading in fog computing framework leveraging multilevel feedback queueing. IEEE Internet Things J 7(7):5773–5782

    Article  Google Scholar 

  27. Kinger Kushagra, Singh Ajeet, Panda Sanjaya Kumar (2022) Priority-aware resource allocation algorithm for cloud computing. In Proceedings of the 2022 Fourteenth International Conference on Contemporary Computing, pp 168–174

  28. Wei Zhiwei, Li Bing, Zhang Rongqing, Cheng Xiang, Yang Liuqing(2022) Dynamic many-to-many task offloading in vehicular fog computing: A multi-agent drl approach. In GLOBECOM 2022-2022 IEEE Global Communications Conference.IEEE, pp 6301–6306

  29. Wei Zhiwei, Li Bing, Zhang Rongqing, Cheng Xiang, Yang Liuqing (2023) Many-to-many task offloading in vehicular fog computing: a multi-agent deep reinforcement learning approach. IEEE Trans Mob Comput 23(3):2107–2122

    Article  Google Scholar 

  30. Singh Simar Preet, Kumar Rajesh, Sharma Anju, Abawajy Jemal H, Kaur Ravneet (2022) Energy efficient load balancing hybrid priority assigned laxity algorithm in fog computing. Clust Comput 25(5):3325–3342

    Article  Google Scholar 

  31. Kelly Frank (1997) Charging and rate control for elastic traffic. Eur Trans Telecommun 8(1):33–37

    Article  Google Scholar 

  32. Capozzi Francesco, Piro Giuseppe, Grieco Luigi Alfredo, Boggia Gennaro, Camarda Pietro (2012) Downlink packet scheduling in lte cellular networks: key design issues and a survey. IEEE Commun Surv Tutorials 15(2):678–700

    Article  Google Scholar 

  33. Chiu Dah Ming(1984) A quantitative measure of fairness and discrimination for resource allocation in shared computer systems. Technical report, Digital Equipment Corporation

Download references

Acknowledgements

Not applicable.

Funding

Not applicable.

Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, National Institute of Technology Warangal, Warangal, Telangana, 506004, India

    Sanjaya Kumar Panda, Thanmayee Pounjula & Bhargavi Ravirala

  2. Department of Software Systems and Cybersecurity, Monash University, Melbourne, Australia

    David Taniar

Authors
  1. Sanjaya Kumar Panda
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Thanmayee Pounjula
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Bhargavi Ravirala
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. David Taniar
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All authors have made significant contributions in developing the algorithm and writing the paper thereafter. Sanjaya Kumar Panda wrote the main manuscript and performed the simulation. Thanmayee Pounjula and Bhargavi Ravirala helped in coding and analyzing the results. David Taniar conceptualized the idea, wrote the algorithms and helped in the simulation. All authors reviewed the manuscript thoroughly.

Corresponding authors

Correspondence to Sanjaya Kumar Panda or David Taniar.

Ethics declarations

Conflict of interest

All authors in this work declared that they have no conflict of interest.

Ethics approval and consent to participate

All authors have participated in this study, and all ethics have been taken into consideration.

Consent to publish

All authors have agreed to submit this version of the paper for publication.

Human and animal ethics

Not applicable.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Panda, S.K., Pounjula, T., Ravirala, B. et al. An energy, delay and priority-aware task offloading algorithm for fog computing incorporating load balancing. J Supercomput 81, 52 (2025). https://doi.org/10.1007/s11227-024-06557-0

Download citation

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11227-024-06557-0

Keywords