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<p>Technological advancements have heightened the demand for real-time applications with minimal energy consumption on resource-constrained devices, often facing storage, computational power, and battery life limitations. Multi-access edge computing mitigates these challenges by offloading data and computational tasks to nearby edge servers, improving task execution efficiency. Despite the progress in task-offloading techniques, real-time processing and energy consumption issues remain. Lyapunov optimization offers a promising approach to address these challenges by optimizing task allocation and resource management in dynamic environments. This paper provides a comprehensive review of task offloading techniques using Lyapunov optimization, focusing on energy consumption and latency. It examines these techniques through classification, theoretical frameworks, and mathematical analyses, while also detailing Lyapunov optimization algorithms, workflows, advantages, and metrics. The paper includes an in-depth comparative analysis of Lyapunov-based algorithms in the context of task offloading, highlighting their benefits and challenges. Finally, it identifies emerging research opportunities and suggests future directions based on recent advancements in the field.</p>

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An Extensive Investigation on Lyapunov Optimization-based Task Offloading Techniques in Multi-access Edge Computing

  • 期刊论文

  • 发表日期：

    2025年6月30日

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  • Vandna Rani Verma,
  • Pushkar,
  • Bablu kumar,
  • Anshul Verma,
  • Vishnu Sharma,
  • Pankaj Kumar Tripathi

摘要

Technological advancements have heightened the demand for real-time applications with minimal energy consumption on resource-constrained devices, often facing storage, computational power, and battery life limitations. Multi-access edge computing mitigates these challenges by offloading data and computational tasks to nearby edge servers, improving task execution efficiency. Despite the progress in task-offloading techniques, real-time processing and energy consumption issues remain. Lyapunov optimization offers a promising approach to address these challenges by optimizing task allocation and resource management in dynamic environments. This paper provides a comprehensive review of task offloading techniques using Lyapunov optimization, focusing on energy consumption and latency. It examines these techniques through classification, theoretical frameworks, and mathematical analyses, while also detailing Lyapunov optimization algorithms, workflows, advantages, and metrics. The paper includes an in-depth comparative analysis of Lyapunov-based algorithms in the context of task offloading, highlighting their benefits and challenges. Finally, it identifies emerging research opportunities and suggests future directions based on recent advancements in the field.