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.

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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
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article

Semantic QoS-aware Resource Allocation for IoV Computation Offloading using Layer Enhanced Whale Optimization Algorithm

Ningbo Zhang, Chuan Yi Tang
1 citations
IoT and Edge/Fog Computing
0.35
article

Semantic QoS-aware Resource Allocation for IoV Computation Offloading using Layer Enhanced Whale Optimization Algorithm

Ningbo Zhang, Chuan Yi Tang
article en
1 citations

Abstract

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.

Beijing University of Posts and Telecommunications (CN)
Openalex Percentile: Top 33%
IoT and Edge/Fog Computing
0.35
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