Skip to main content

Advertisement

Springer Nature Link
Log in

An improved multi-objective evolutionary algorithm for computation offloading in the multi-cloudlet environment

  • Letter
  • Published:
Frontiers of Computer Science Aims and scope Submit manuscript

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

References

  1. Khan A U R, Othman M, Madani S A. A survey of mobile cloud computing application models. IEEE Communications Surveys and Tutorials, 2014, 16(1): 393–413

    Article  Google Scholar 

  2. Sanaei Z, Abolfazli S, Gani A. Heterogeneity in mobile cloud computing: taxonomy and open challenges. IEEE Communications Surveys and Tutorials, 2014, 16(1): 369–392

    Article  Google Scholar 

  3. Zhang W, Guo B, Shen Y. An energy-efficient algorithm for multi-site application partitioning in MCC. Sustainable Computing: Informatics and Systems, 2018, 18: 45–53

    Google Scholar 

  4. Bandyopadhyay S, Saha S. A simulated annealing-based multi-objective optimization algorithm: AMOSA. IEEE Transactions on Evolutionary Computation, 2008, 12(3): 269–283

    Article  Google Scholar 

  5. Deb K, Pratap A, Agarwal S. A fast and elitist multi-objective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation, 2002, 6(2): 182–197

    Article  Google Scholar 

  6. Liu L, Gu S X, Fu D M. A new multi-objective evolutionary algorithm for inter cloud service composition. KSII Transactions on Internet and Information Systems, 2018, 12(1): 1–20

    Google Scholar 

  7. Zhang Q F, Li H. MOEA/D: a multiobjective evolutionary algorithm based on decomposition. IEEE Transactions on Evolutionary Computation, 2008, 11(6): 712–731

    Article  Google Scholar 

  8. Li H, Zhang Q F. Multi-objective optimization problems with complicated pareto sets, MOEA/D and NSGA-II. IEEE Transactions on Evolutionary Computation, 2009, 13(2): 284–302

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant Nos. 61772068, 61370132 and 61472033).

Author information

Authors and Affiliations

  1. Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, 100083, China

    Li Liu & Yuanyuan Du

  2. Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, University of Science and Technology Beijing, Beijing, 100083, China

    Li Liu

Authors
  1. Li Liu
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Yuanyuan Du
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding author

Correspondence to Li Liu.

Electronic supplementary material

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Liu, L., Du, Y. An improved multi-objective evolutionary algorithm for computation offloading in the multi-cloudlet environment. Front. Comput. Sci. 15, 155503 (2021). https://doi.org/10.1007/s11704-020-9346-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11704-020-9346-z