面向延迟感知的车联网缓存优化策略
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摘要：
车联网技术的发展催生了各种数据密集型和延迟敏感型的车载应用。将内容缓存在用户侧，可为车载应用提供高效的内容交付。研究了车联网中以用户为中心的内容交付问题，提出了一种基于延迟感知的内容缓存优化策略，通过协同路边单元和车载单元，在不确定请求内容的情况下最小化传输时延。首先基于多准则决策收集缓存车辆特征信息，确定最佳缓存车辆；然后提出了一种基于流行度的动态内容缓存算法，获取最优内容缓存决策。仿真实验表明，与其他方案相比，所提策略可有效提高缓存命中率，减少时延。
The development of vehicular networking technology has given rise to various data-intensive and latency-sensi-tive in-vehicle applications. Caching content at the user side can enable efficient content delivery for these applications. This paper investigates the user-centric content delivery problem in vehicular networks and proposes a latency-aware content caching optimization strategy, which minimizes transmission delays by coordinating roadside units( RSUs) and onboard units(OBUs) under uncertain content requests.First, basing on multi-criteria decision-making, we collects caching vehicle characteristics to determine the optimal caching vehicle. Then, a popularity-based dynamic content caching algorithm is proposed to derive the optimal caching strategy, Simulation results demonstrate that, compared with other schemes, the proposed strategy effectively improves cache hit rates while reducing content delivery latency.
作者:
王亚丽，韩晓培
Wang Yali,Han Xiaopei
机构地区：
苏州城市学院计算科学与人工智能学院；计算机与信息工程学院
引用本文：
王亚丽，韩晓培。面向延迟感知的车联网缓存优化策略[J].学报(自然科学版),2025,53(6):7483.( Wang Yali, Han Xiaopei.An optimization strategy for latency-aware internet of vehicle caching[J].Journal of Henan Normal University( Natural Science Edition),2025,53(6):74-83.DOI:10.16366/j.cnki.1000-2367.2024.07.12.0001.)
基金：
国家自然科学基金
关键词：
边缘缓存；移动边缘计算；车联网；协作缓存
edge caching; mobile edge computing; internet of vehicles; collaborative cache
分类号：
TP391
