Semantic-Aware Offloading in Mobile Edge Computing: A Survey

Mobile Edge Computing (MEC) has become essential for minimizing latency and enhancing network efficiency by bringing computational resources closer to the user. The advent of 6G networks has introduced semantic communication, which focuses on the meaning of transmitted data rather than mere bit transmission, aiming to optimize communication efficiency. In this context, offloading computational tasks in semantic communication based MEC systems presents new challenges, including managing the energy required for semantic extraction, optimizing user-edge association, and balancing accuracy with efficiency. This survey provides a comprehensive review of these challenges and the solutions proposed in recent research. By analyzing the convergence of semantic communication and MEC, we identify critical technical requirements and explore various algorithms designed to address these challenges. The paper also highlights open research areas, such as scalability, dynamic adaptation, energy-efficiency trade-offs, and the security of semantic data. These insights offer valuable guidelines for future research and practical implementations in this evolving field.

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Publication Details

Published
2024-10-16
DOI
https://doi.org/10.1109/ictc62082.2024.10826704
Citations
1
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
0.35
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article

Semantic-Aware Offloading in Mobile Edge Computing: A Survey

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1 citations
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article

Semantic-Aware Offloading in Mobile Edge Computing: A Survey

Hyung Tae Lee, Hyosu Kim, Sungrae Cho, Jeongyeup Paek, Yongseok Son, Dongwook Won
article en
1 citations

Abstract

Mobile Edge Computing (MEC) has become essential for minimizing latency and enhancing network efficiency by bringing computational resources closer to the user. The advent of 6G networks has introduced semantic communication, which focuses on the meaning of transmitted data rather than mere bit transmission, aiming to optimize communication efficiency. In this context, offloading computational tasks in semantic communication based MEC systems presents new challenges, including managing the energy required for semantic extraction, optimizing user-edge association, and balancing accuracy with efficiency. This survey provides a comprehensive review of these challenges and the solutions proposed in recent research. By analyzing the convergence of semantic communication and MEC, we identify critical technical requirements and explore various algorithms designed to address these challenges. The paper also highlights open research areas, such as scalability, dynamic adaptation, energy-efficiency trade-offs, and the security of semantic data. These insights offer valuable guidelines for future research and practical implementations in this evolving field.

Chung-Ang University (KR)
Openalex Percentile: Top 34%
IoT and Edge/Fog Computing
0.35
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