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Left-Right-Front Caching Strategy for Vehicular Networks in ICN-Based Internet of Things

机译:基于ICN的Internet的车辆网络左前端缓存策略

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In Vehicular Ad-hoc Networks (VANET), vehicles act like mobile nodes for fetching, sharing, and disseminating important information related to vehicle safety, warning messages, emergency events, and passenger infotainment. Due to continuous information sharing of vehicles with their surrounding nodes, Road Side Units (RSUs), and infrastructures, the existing host-centric IP-based network cannot fulfill the requirements of VANETs. Therefore, Information Centric Networking (ICN) architectures are the introduced to comprehensively address the problems of Internet of Things (IoT)-based VANETs, known as VANET-IoT. This paper introduces a new ICN-based proactive left-right-front (LRF) caching strategy for VANETs, which maximizes the performance of VANETs by placing content proactively at the right nodes. The proposed strategy also provides a mechanism for the timely dissemination of safety-related messages. LRF is compared with other caching strategies in the NS-3 simulator, which outperforms those schemes in terms of cache utilization, hop ratios, and resolved interest ratios with respect to 100 MB, 500 MB, and 1 GB cache sizes.
机译:在车载ad-hoc网络(VANET)中,车辆类似于移动节点,用于获取,共享和传播与车辆安全,警告消息,紧急事件和乘客信息娱乐有关的重要信息。由于持续信息共享车辆与周围节点,道路侧单元(RSU)和基础设施,现有的主机基于IP的网络无法满足VANET的要求。因此,信息中心网络(ICN)架构是介绍的,以全面地解决了基于事物互联网(IOT)的vanets的问题,称为VANET-IOT。本文介绍了一种新的ICN的主动左前方(LRF)Vanets缓存策略,可通过在正确的节点上积极放置内容来最大限度地提高VAINET的性能。拟议的策略还提供了一种及时传播安全相关信息的机制。将LRF与NS-3模拟器中的其他缓存策略进行比较,这在高速缓存利用率,跳率和分辨的兴趣比率方面优于100 MB,500 MB和1 GB高速缓存大小。

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