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Secure and Efficient Task Offloading with Resource Allocation in Vehicular Edge Computing

delete2026-01-01
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PRE
AI
B
Bo Wu
Y
Yuyin Ma
T
Tingyan Long *
L
Liang Wan
J
Jiong Dong
Y
Yijun Lu
赵静 封面图
赵静 (J. Zhao)
DOI：10.1007/978-981-95-3480-7_11delete
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摘要

摘要

En 中文
车载边缘计算系统整合车辆的计算资源，并为其他车辆和行人提供任务卸载服务。然而，在确保车辆任务卸载低响应时延的同时，车载网络还需要将上下文信息（如车辆速度和位置）上传至路侧单元和基站，这给车载网络隐私带来了显著威胁和风险。本文提出了一种基于近端策略优化方法（Proximal Policy Optimization）的任务卸载、数据安全和资源分配卸载算法（TDR-PPO）。为保障传输数据的安全性，TDR-PPO通过选择合适的加密算法以最小化所有任务的平均失败概率。实验结果表明，所提出的方法在平均时延和数据失败概率方面显著优于基准算法，凸显其在动态车辆边缘计算中平衡性能与安全性的有效性。
Keyword:
Vehicular edge computing
Task offloading
Data security
Resource allocation
Proximal policy optimization

期刊

B
BLOCKCHAIN AND TRUSTWORTHY SYSTEMS, BLOCKSYS 2025, PT III
IF:
0
论文数:
28
被引数:
0

机构

B
beijing university of posts & telecommunications
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1.4W
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被引数: 9
W
Waseda University
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1.0W
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G
guizhou university
学者数:
2.5W
论文数: 1.3W
被引数: 15
X
xuchang university
学者数:
379
论文数: 144
被引数: 0
X
xinjiang university
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论文数: 1.2K
被引数: 0
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