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arXiv · 2309.11736

Resource Allocation for Semantic-Aware Mobile Edge Computing Systems

Yihan Cang·Ming Chen·Zhaohui Yang·Yuntao Hu·Yinlu Wang·Zhaoyang Zhang·Kai-Kit Wong
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Abstract

In this paper, a semantic-aware joint communication and computation resource allocation framework is proposed for mobile edge computing (MEC) systems. In the considered system, each terminal device (TD) has a computation task, which needs to be executed by offloading to the MEC server. To further decrease the transmission burden, each TD sends the small-size extracted semantic information of tasks to the server instead of the large-size raw data. An optimization problem of joint semantic-aware division factor, communication and computation resource management is formulated. The problem aims to minimize the maximum execution delay of all TDs while satisfying energy consumption constraints. The original non-convex problem is transformed into a convex one based on the geometric programming and the optimal solution is obtained by the alternating optimization algorithm. Moreover, the closed-form optimal solution of the semantic extraction factor is derived. Simulation results show that the proposed algorithm yields up to 37.10% delay reduction compared with the benchmark algorithm without semantic-aware allocation. Furthermore, small semantic extraction factors are preferred in the case of large task sizes and poor channel conditions.

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Yihan Cang, Ming Chen, Zhaohui Yang, Yuntao Hu, Yinlu Wang, Zhaoyang Zhang, Kai-Kit Wong. 2023-09-21. Resource Allocation for Semantic-Aware Mobile Edge Computing Systems. https://arxiv.org/abs/2309.11736

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