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Energy-Efficient Joint Caching and Transcoding for HTTP Adaptive Streaming in 5G Networks with Mobile Edge Computing

机译:具有移动边缘计算功能的5G网络中HTTP自适应流的节能联合缓存和转码

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With the HTTP adaptive video streaming (HAS) transmission over mobile networks being widely concerned and the new promising technique of mobile edge computing (MEC) emerging, the problem of HAS transmission in MEC-based 5G networks has been widely studied. However, most of them focus on the issues of network resource utilization and the quality of experience (QoE) promotion, while the problem of energy efficiency is largely ignored. In this paper, different from previous works, by taking the caching and transcoding into consideration, we propose a joint caching and transcoding schedule strategy for HAS delivery in MEC-enhanced 5G network to realize the energy efficiency. We formulate the problem of energy efficient joint caching and transcoding as an integer linear programming problem to minimize the system energy consumption. Then to make the NP-hard problem tractable, we introduce a heuristic scheme based on simulated annealing algorithm to iteratively provide the global optimum solution. Finally, simulation results are illustrated to show that our proposed strategy presents an excellent performance and provides practical significance to choose proper ways of responding users' content requests according to different hit modes.
机译:利用HTTP自适应视频流(具有)通过移动网络传输广泛关注和移动边缘计算(MEC)新兴的新有前景技术,已经广泛研究了基于MEC的5G网络中的传输的问题。然而,大多数人都专注于网络资源利用的问题和经验质量(QoE)促销,而能源效率的问题在很大程度上被忽略了。在本文中,与以前的作品不同,通过考虑缓存和转码,我们提出了一个联合缓存和转码时间表策略,用于在MEC增强的5G网络中交付,实现能源效率。我们制定节能关节缓存和转码作为整数线性规划问题的问题,以最大限度地减少系统能源消耗。然后为了使NP-Hard问题易于解决,我们介绍了一种基于模拟退火算法的启发式方案,以迭代提供全局最佳解决方案。最后,说明了模拟结果表明,我们的拟议策略提出了优异的性能,并提供了根据不同的命中模式选择响应用户内容请求的适当方式的现实意义。

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