TY  - GEN
PB  - Institute of Electrical and Electronics Engineers (IEEE)
AV  - public
N2  - 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.
EP  - 1590
N1  - This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions.
TI  - Resource Allocation for Semantic-Aware Mobile Edge Computing Systems
SP  - 1585
ID  - discovery10191115
Y1  - 2023///
UR  - http://dx.doi.org/10.1109/gcwkshps58843.2023.10464965
A1  - Cang, Y
A1  - Chen, M
A1  - Yang, Z
A1  - Hu, Y
A1  - Wang, Y
A1  - Zhang, Z
A1  - Wong, KK
ER  -