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Hybrid Immune Whale Differential Evolution Optimization (HIWDEO) Based Computation Offloading in MEC for IoT

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Abstract

The adoption of User Equipment (UE) is on the rise, driven by advancements in Mobile Cloud Computing (MCC), Mobile Edge Computing (MEC), the Internet of Things (IoT), and Artificial Intelligence (AI). Among these, MEC stands out as a pivotal aspect of the 5G network. A critical challenge within the realm of MEC is task offloading. This involves optimizing conflicting factors like execution time, energy usage, and computation duration. Additionally, addressing the offloading of interdependent tasks poses another significant hurdle that requires attention. The developed models are single objective, task dependency, and computationally expensive. As a result, the Immune whale differential evolution optimization algorithm is proposed to offload the dependent tasks to the MEC with three objectives: minimizing the execution delay and reducing the energy and cost of MEC resources. The standard Whale optimization is incorporated with DE with customized mutation operations and immune system to enhance the searching strategy of Whale optimization. The proposed HIWDEO secured reduced energy and overhead of UE to execute its tasks. The comparison between the developed model and other optimization approaches shows the superiority of HIWDEO.

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Data Availability

The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.

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Funding

This research received no specific grant from any funding agency.

Author information

Author notes

  1. Jizhou Li and Qi Wang made equal contributions to the manuscript. They worked together.

Authors and Affiliations

  1. Ulster College at Shaanxi University of Science & Technology, Xi’an, 710021, Shanxi, China

    Jizhou Li

  2. Computer Science & Artificial Intelligence Laboratory, Guangdong Institute of Advanced Technology Chinese Academy of Sciences, Shenzheng, 518055, Guangdong, China

    Qi Wang

  3. College of Software, North University of China, Taiyuan, 030051, Shanxi, China

    Shuai Hu

  4. Co11ege of Economics and Management, TianJin University of Science and Technology, Tianjin, 710021, Shanxi, China

    Ling Li

Authors
  1. Jizhou Li
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  2. Qi Wang
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Contributions

Jizhou Li: Conceptualization, Methodology, Formal analysis, Supervision, Writing—original draft, Writing—review & editing.

Qi Wang: Writing—original draft, Writing—review & editing.

Shuai Hu: Investigation, Data Curation, Validation, Resources, Writing—review & editing.

Ling Li: Investigation, Data Curation, Validation, Resources, Writing—review & editing.

Corresponding author

Correspondence to Qi Wang.

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Li, J., Wang, Q., Hu, S. et al. Hybrid Immune Whale Differential Evolution Optimization (HIWDEO) Based Computation Offloading in MEC for IoT. J Grid Computing 21, 70 (2023). https://doi.org/10.1007/s10723-023-09705-7

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