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Multimedia service utilizing hierarchical fog computing for vehicular networks

机译:利用分层雾计算的车载网络多媒体服务

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This paper focuses on the enhancement of multimedia streaming services for passengers travelling in vehicles. Online media streaming and sharing is popular and has increased tremendously these days whether it is used at home, in the office or while travelling. The millions of internet users accessing media contents consumes a huge bandwidth and can create Internet bottlenecks or traffic congestion. Media traffic like videos flowing from such congested links can introduce even higher delays increasing buffering time. This can bring a bad Quality of Service (QoS) and bad Quality of Experience (QoE) to users. Such degradation is seen even more when streaming requests are sent by clients within mobile nodes like vehicles. To tackle this issue this paper proposes a hierarchical fog computing based multimedia streaming that reduces latency and minimizes Internet bandwidth consumption. A simulation was conducted for the performance evaluation of the proposed architecture and video streaming service was considered for evaluation. The result acquired from the simulation showed that proposed architecture enhances the QoS and brings better QoE to users.
机译:本文着重于为乘车旅行的乘客增强多媒体流服务。在线媒体流和共享很流行,并且无论是在家中,办公室还是在旅途中使用时,近来都在迅速增长。数百万访问媒体内容的Internet用户消耗大量带宽,并且会造成Internet瓶颈或流量拥塞。从拥塞的链接中流出的视频之类的媒体流量可能会引入更高的延迟,从而增加缓冲时间。这会给用户带来不良的服务质量(QoS)和不良的体验质量(QoE)。当流请求由移动节点(如车辆)内的客户端发送时,这种降级现象更加明显。为了解决这个问题,本文提出了一种基于分层雾计算的多媒体流,该流可减少延迟并最大程度地减少Internet带宽消耗。针对所提出的架构的性能评估进行了仿真,并考虑了视频流服务进行评估。从仿真中获得的结果表明,所提出的体系结构增强了QoS,并为用户带来了更好的QoE。

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