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An Adaptive Video Transmission Mechanism over MEC-Based Content-Centric Networks

机译:基于MEC的内容网络网络的自适应视频传输机制

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The rapid growth of video traffic poses serious challenges to the current Internet. Content-Centric Networking (CCN) as a promising candidate has been proposed to reengineer the Internet architecture. The in-network caching and named content communication model of CCN can enhance the video streaming applications and reduce the network workload. Due to the bandwidth-consuming characteristic of video streaming, the aggressive transmission of video data will cause a reduction of overall network efficiency. In this paper, we present an adaptive video transmission mechanism over Mobile Edge Computing- (MEC-) based CCN. The computation and storage resources of the MEC server are utilized to facilitate the video delivery. Our mechanism adopts a scalable video coding scheme to adaptively control transmission rate to cope with the network condition variation. To analyse the equilibrium property of the proposed mechanism, an analytical model is deduced by using network utility function and convex programming. We also take into account the packet loss in wired and wireless links and present a MEC assistant loss recovery algorithm. The experiment results demonstrate the performance improvement of our proposed mechanism.
机译:视频交通的快速增长对当前的互联网带来了严重的挑战。已经提出了以内容为中心的网络(CCN)作为一个有希望的候选人来重新进入互联网架构。 CCN的网络内高速缓存和命名内容通信模型可以增强视频流应用并减少网络工作负载。由于视频流的带​​宽特性,视频数据的攻击传输将导致整体网络效率降低。在本文中,我们在基于移动边缘计算(MEC-)的CCN上呈现了一种自适应视频传输机制。利用MEC服务器的计算和存储资源来促进视频传送。我们的机制采用可伸缩的视频编码方案,以自适应地控制传输速率以应对网络条件变化。为了分析所提出机制的平衡性,通过使用网络实用功能和凸编程推断出分析模型。我们还考虑到有线和无线链路中的数据包丢失,并呈现MEC辅助丢失恢复算法。实验结果表明了我们所提出的机制的性能提高。

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