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Optimization Method of Fog Computing High Offloading Service Based on Frame of Reference

Author

Listed:
  • Deng Li

    (School of Electronic Information, Central South University, Changsha 410075, China)

  • Chengqin Yu

    (School of Electronic Information, Central South University, Changsha 410075, China)

  • Ying Tan

    (School of Electronic Information, Central South University, Changsha 410075, China)

  • Jiaqi Liu

    (School of Electronic Information, Central South University, Changsha 410075, China)

Abstract

The cost of offloading tasks is a crucial parameter that influences the task selection of fog nodes. Low-cost tasks can be completed quickly, while high-cost tasks are rarely chosen. Therefore, it is essential to design an effective incentive mechanism to encourage fog nodes to actively participate in high-cost offloading tasks. Current incentive mechanisms generally increase remuneration to enhance the probability of participants selecting high-cost tasks, which inevitably leads to increased platform costs. To improve the likelihood of choosing high-cost tasks, we introduce a frame of reference into fog computing offloading and design a Reference Incentive Mechanism (RIM) by incorporating reference objects. Leveraging the characteristics of the frame of reference, we set an appropriate reference task as the reference point that influences the attraction of offloading tasks to fog nodes and motivates them towards choosing high-cost tasks. Finally, simulation results demonstrate that our proposed mechanism outperforms existing algorithms in enhancing the selection probability of high-cost tasks and improving platform utility.

Suggested Citation

  • Deng Li & Chengqin Yu & Ying Tan & Jiaqi Liu, 2024. "Optimization Method of Fog Computing High Offloading Service Based on Frame of Reference," Mathematics, MDPI, vol. 12(5), pages 1-19, February.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:5:p:621-:d:1342102
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    References listed on IDEAS

    as
    1. Alexander Chernev, 2005. "Context Effects without a Context: Attribute Balance as a Reason for Choice," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 32(2), pages 213-223, September.
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