论文标题
在车辆网络中用于视频传输的内容驱动的资源分配方案
A Content Driven Resource Allocation Scheme for Video Transmission in Vehicular Networks
论文作者
论文摘要
随着计算机视觉应用的不断增长，许多视频被传输用于内容分析，分配资源的方法可能会影响视频内容分析的性能。为此，在车辆网络中用于视频传输的传统资源分配方案，例如基于质量的服务（QoS）或基于体验质量（QOE）方案，不再是最佳的。在本文中，我们为在带宽限制下配备相机配备的车辆的有效内容驱动的资源分配方案，以提高视频内容分析性能。提出的资源分配方案基于最大化质量质量（QOC），这与内容分析性能有关。首先提出了基于QOC的评估模型。然后，将资源分配问题转换为可解决的凸优化问题。最后，模拟结果表明，与基于QOE的方案（如基于QOE）相比，我们提出的方案的性能更好。
With the growing computer vision applications, lots of videos are transmitted for content analysis, the way to allocate resources can affect the performance of video content analysis. For this purpose, the traditional resource allocation schemes for video transmission in vehicular networks, such as qualityof-service (QoS) based or quality-of-experience (QoE) based schemes, are no longer optimal anymore. In this paper, we propose an efficient content driven resource allocation scheme for vehicles equipped with cameras under bandwidth constraints in order to improve the video content analysis performance. The proposed resource allocation scheme is based on maximizing the quality-of-content (QoC), which is related to the content analysis performance. A QoC based assessment model is first proposed. Then, the resource allocation problem is converted to a solvable convex optimization problem. Finally, simulation results show the better performance of our proposed scheme than the existing schemes like QoE based schemes.
