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A comprehensive review on internet of things task offloading in multi-access edge computing.

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Summary

This review synthesizes Internet of Things (IoT) task offloading in Multi-access Edge Computing (MEC). It analyzes algorithms and mechanisms, identifying research gaps and future trends for IoT devices in MEC networks.

Keywords:
Computation offloadingInternet of thingsMobile edge computingMulti-access edge computingTask offloading

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Network Engineering

Background:

  • Internet of Things (IoT) devices face limitations in computing capacity and battery life.
  • Multi-access Edge Computing (MEC) offers a solution by enabling task offloading to nearby edge servers.
  • Existing reviews lack a specific focus on IoT task offloading within MEC environments.

Purpose of the Study:

  • To provide a comprehensive understanding of IoT task offloading algorithms and mechanisms in MEC networks.
  • To analyze existing research by categorizing mechanisms, evaluation methods, and supported parameters.
  • To identify current research shortcomings and outline future research directions in MEC for IoT.

Main Methods:

  • Systematic literature review of IoT task offloading in MEC.
  • Extraction and analysis of key information from reviewed papers, including problems solved, technical classifications, evaluation methods, and parameters.
  • Synthesis of findings to identify trends and gaps.

Main Results:

  • Detailed analysis of various IoT task offloading algorithms and mechanisms in MEC.
  • Classification of techniques based on problem-solving, technical approach, and evaluation metrics.
  • Identification of limitations in current research and potential areas for advancement.

Conclusions:

  • The study highlights the critical need for focused research on IoT task offloading within MEC frameworks.
  • It offers a structured overview to guide researchers in understanding the current landscape and pursuing novel research paths.
  • This review serves as a foundational resource for developing efficient and effective MEC solutions for IoT devices.