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QoS-Aware Hierarchical Web Caching Scheme for Online Video Streaming Applications in Internet-Based Vehicular Ad Hoc Networks

机译:基于Internet的车载Ad Hoc网络中在线视频流应用程序的QoS感知分层Web缓存方案

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摘要

Many applications, such as intelligent transport system and mobile multimedia, use Internet-based vehicular ad hoc networks (IVANETs). In IVANETs, users often access multimedia content from anywhere using Internet connectivity to remote video streaming servers. Due to the high mobility of the nodes in IVANETs, however, maintaining quality of service (QoS) for these video streaming applications with respect to parameters such as jitter, throughput, buffering, and transmission delays is a challenging task. To address these challenges, we propose a new QoS-aware hierarchical web caching (QHWC) scheme in IVANETs. We propose two new metrics, namely, load utilization ratio (LUR) and query to connectivity ratio (QCR), to maintain the QoS for various video streaming applications in IVANETs. We compare the performance of our proposed QHWC scheme with past approaches, such as dynamic service, weighted segment, and machine learning based, using various parameters such as QCR, communication cost, query delay, cache hit ratio, query generation rate, invalidation cost, and cache update interval. Our results demonstrate that the proposed QHWC scheme yields an average decrease of 16.75% and 22% in communication cost and query relay, respectively, and an average increase of 9.31% in cache hit ratio. Moreover, the invalidation cost reduces by 26.26% (on average) in our proposed scheme compared with other schemes.
机译:许多应用程序,例如智能运输系统和移动多媒体,都使用基于Internet的车辆自组织网络(IVANET)。在IVANET中,用户经常使用Internet连接到远程视频流服务器从任何地方访问多媒体内容。但是,由于IVANET中节点的高度移动性,因此,就这些视频流应用程序而言,就诸如抖动,吞吐量,缓冲和传输延迟之类的参数保持服务质量(QoS)是一项艰巨的任务。为了解决这些挑战,我们在IVANET中提出了一种新的QoS感知的分层Web缓存(QHWC)方案。我们提出了两个新的指标,即负载利用率(LUR)和查询连接率(QCR),以维护IVANET中各种视频流应用程序的QoS。我们使用各种参数(例如QCR,通信成本,查询延迟,缓存命中率,查询生成率,无效成本,比较方法)将我们提出的QHWC方案的性能与过去的方法(例如动态服务,加权分段和基于机器学习)的性能进行了比较和缓存更新间隔。我们的结果表明,提出的QHWC方案分别使通信成本和查询中继平均减少了16.75%和22%,高速缓存命中率平均增加了9.31%。此外,与其他方案相比,我们提出的方案中的无效成本平均降低了26.26%。

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