基于雾计算基础设施的qos感知流服务

Chin-Feng Lai, Dong-Yu Song, Ren-Hung Hwang, Ying-Xun Lai
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引用次数: 20

摘要

云计算技术逐渐将每一项服务都实现了在线,使服务的所有数据和信息都存储在云存储中。但是,有些实时业务(如多媒体流媒体和紧急通知)需要敏感的响应和低延迟。对于云计算而言,终端用户与云之间的数据传输大大增加了响应延迟,限制了用户覆盖范围,从而阻碍了云流服务实现高用户服务质量。为此,提出了一种基于雾计算基础设施的qos感知流媒体服务,通过使视频适应当前网络条件并可能利用本地计算资源来缓解传统的内容交付问题。雾计算旨在扩展云网络的边缘,以减少延迟和网络拥塞。实验结果表明,该机制使服务提供商能够通过整合来自不同层的信息来提高资源利用率和服务质量,从而在雾计算基础设施上以最佳质量交付和调整视频。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A QoS-aware streaming service over fog computing infrastructures
The cloud computing technology gradually brings every service online that makes all data and information of services is stored in cloud storage. However, there are real-time services such as multimedia streaming and emergency notification that require sensitive response and low latency. Regarding of the cloud computing, the data transmission between the end-users and the cloud significantly increases the response latency and limits the user coverage, thus preventing cloud streaming services to achieve high user quality of service. To this end, a QoS-aware streaming service over fog computing infrastructures is proposed to relieve the traditional content delivery issues by adapting the video to the current network conditions and possibly exploiting local computing resources. Fog computing is designed to extend the edge of the cloud network in order to decrease the latency and network congestion. Experimental results show the proposed mechanism enables service providers to improve resource utilization and quality of service by incorporating information from different layers in order to deliver and adapt a video in its best possible quality over fog computing infrastructures.
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