Scholarlink

<p>Computation offloading is a key technology in Multi-access Edge Computing (MEC) that compensates for the limitations of multiple devices in terms of energy efficiency, processing power, and storage capacity. On the other hand, task request computation offloading reduces the delay caused by long-distance data transfer while simultaneously reducing communication strain on core networks. However, new 5/6G apps rely on computation offloading technologies to deliver efficient services to users. Using a variety of significant methodologies, both industry and academia have recently conducted a large number of studies on compute offloading strategies in MEC networks. This review paper offers a thorough exploration of computation offloading in MEC networks. It discusses applications, objectives, and methodologies. It highlights the challenges in attaining numerous offloading&#xa0;goals, such as minimizing delays, conserving energy, and increasing&#xa0;revenue. It also discusses the specific challenges faced in this field and investigates potential uses for computational offloading in MEC systems. The issues related to computational offloading methods were investigated in order to overcome the limitations within the MEC system. The comparative analysis focuses on particular applications and discusses the advantages and disadvantages of each strategy. Finally, the present difficulties and potential solutions for compute offloading in MEC networks are examined from four perspectives: subtask dependence and online task requests, server selection, real-time environment awareness, and security.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

An in-depth analysis of computation offloading approaches in multi-access edge computing systems

  • 期刊论文

  • 发表日期：

    2025年6月20日

查看全文
  • V Srinivas Lokavarapu,
  • Kunjam Nageswara Rao,
  • Sitaratnam Gokuruboyina,
  • Shiva Shankar Reddy

摘要

Computation offloading is a key technology in Multi-access Edge Computing (MEC) that compensates for the limitations of multiple devices in terms of energy efficiency, processing power, and storage capacity. On the other hand, task request computation offloading reduces the delay caused by long-distance data transfer while simultaneously reducing communication strain on core networks. However, new 5/6G apps rely on computation offloading technologies to deliver efficient services to users. Using a variety of significant methodologies, both industry and academia have recently conducted a large number of studies on compute offloading strategies in MEC networks. This review paper offers a thorough exploration of computation offloading in MEC networks. It discusses applications, objectives, and methodologies. It highlights the challenges in attaining numerous offloading goals, such as minimizing delays, conserving energy, and increasing revenue. It also discusses the specific challenges faced in this field and investigates potential uses for computational offloading in MEC systems. The issues related to computational offloading methods were investigated in order to overcome the limitations within the MEC system. The comparative analysis focuses on particular applications and discusses the advantages and disadvantages of each strategy. Finally, the present difficulties and potential solutions for compute offloading in MEC networks are examined from four perspectives: subtask dependence and online task requests, server selection, real-time environment awareness, and security.