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首页> 外文期刊>Journal of network and computer applications >Collaborative joint caching and transcoding in mobile edge networks
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Collaborative joint caching and transcoding in mobile edge networks

机译:移动边缘网络中的协同联合缓存和代码转换

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摘要

Video streaming has become a leading consumer of network resources in the last decade. Despite considerable developments, video content providers still face major challenges, which include minimizing data transfer from Content Delivery Network (CDN) or origin servers, CDN cost, and video startup delays. Recent edge computing technologies, such as Mobile Edge Computing (MEC) introduces new opportunities for Radio Access Networks (RANs) by providing computing and storage resources at the Mobile Base Stations (MBSs). Caching and processing videos at the edge networks relieve excessive data transfers over the backhaul links and minimize the viewers perceived delay. Collaborative caching and processing strategies have been proposed to efficiently utilize the edge resources, where neighboring MEC servers share the cached videos. However, such strategies introduce new challenges due to excessive backhaul links utilization for video sharing and limited resources. We propose a collaborative joint caching and processing strategy using the X2 network interface for sharing video data among multiple caches. Our design aims to minimize: (a) backhaul links usage for sharing video data, (b) network usage in transferring data from the CDN, (c) the viewer perceived delay, and (d) CDN cost. We also propose to fetch the higher bitrate version video from the origin/CDN servers and transcode it to the requested version on the fly to effectively use the Adaptive Bit Rate (ABR) streaming and online transcoding. This joint caching and processing approach is formulated as a minimization problem, subject to storage, processing, and bandwidth constraints. We also propose an online greedy algorithm that controls video transcoding, sharing using the X2 or backhaul links, and manages video caching and removing at the edge caches. Simulation results prove a better performance of our proposed algorithm compared to the recent edge caching approaches in terms of cost, average delay, cache removal, and cache hit ratio for different configurations.
机译:在过去的十年中,视频流已成为网络资源的主要消费者。尽管取得了长足发展,但视频内容提供商仍面临重大挑战,包括最大程度地减少从内容交付网络(CDN)或原始服务器的数据传输,CDN成本以及视频启动延迟。通过在移动基站(MBS)提供计算和存储资源,诸如移动边缘计算(MEC)之类的最新边缘计算技术为无线电接入网(RAN)带来了新的机遇。在边缘网络上缓存和处理视频可减轻回程链路上过多的数据传输,并最大程度地减少观众的感知延迟。已经提出了协作缓存和处理策略以有效地利用边缘资源,其中相邻的MEC服务器共享缓存的视频。然而,由于过多的回程链路用于视频共享和有限的资源,这样的策略带来了新的挑战。我们提出了使用X2网络接口的协作式联合缓存和处理策略,用于在多个缓存之间共享视频数据。我们的设计旨在最大程度地减少:(a)共享视频数据的回程链路使用;(b)从CDN传输数据时的网络使用;(c)观众察觉到的延迟;以及(d)CDN成本。我们还建议从原始/ CDN服务器中获取更高比特率的视频,并即时将其转码为请求的版本,以有效地使用自适应比特率(ABR)流传输和在线转码。这种联合缓存和处理方法被表述为一个最小化问题,受存储,处理和带宽约束的影响。我们还提出了一种在线贪婪算法,该算法可以控制视频转码,使用X2或回程链接进行共享,并在边缘缓存中管理视频缓存和删除。与最近的边缘缓存方法相比,仿真结果证明了我们提出的算法在不同配置的成本,平均延迟,缓存删除和缓存命中率方面具有更好的性能。

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