Semantic QoS-aware Resource Allocation for IoV Computation Offloading using Layer Enhanced Whale Optimization Algorithm
In the Internet of Vehicles, computation task offloading is essential to meet increasing computational demands. This paper proposes a resource allocation algorithm based on an enhanced Whale Optimization Algorithm (WOA) for semantic communication, dynamically allocating resources based on the semantic quality of tasks. We develop a Semantic-Aware Layer Enhanced Whale Optimization Algorithm (LEWOA) that improves multi-dimensional resource allocation by considering the Quality of Service (QoS) of semantic data. Simulations using the YOLO-V8 framework and HRNet are performed to validate the superiority of the proposed algorithm.
Authors
- Ningbo Zhang (ORCID: https://orcid.org/0000-0002-7007-9741)
- Chuan Yi Tang (ORCID: https://orcid.org/0000-0003-0729-1624)
Institutions
- Beijing University of Posts and Telecommunications (CN)
Publication Details
- Published
- 2024-12-13
- DOI
- https://doi.org/10.1109/iccc62609.2024.10941942
- Citations
- 1
- Primary Topic
- IoT and Edge/Fog Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.35