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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关节缓存和转码

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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:视频流已成为过去十年中的网络资源的主要消费者。尽管有相当大的发展,视频内容提供商仍面临重大挑战,包括最小化来自内容传递网络(CDN)或原点服务器,CDN成本和视频启动延迟的数据传输。最近的边缘计算技术,例如移动边缘计算(MEC)通过在移动基站(MBSS)提供计算机和存储资源来引入无线电接入网络(RAN)的新机会。 EDGE网络中的缓存和处理视频在回程链路上缓解过多的数据传输,并最大限度地减少观众感知延迟。已提出协作缓存和处理策略以有效利用边缘资源,其中邻近MEC服务器共享缓存的视频。然而,由于视频共享和有限资源的过度回程利用率,此类策略引入了新的挑战。我们提出了一种使用X2网络接口的协同联合缓存和处理策略,用于在多个高速缓存之间共享视频数据。我们的设计旨在最大限度地减少:(a)回程链路用于共享视频数据的使用,(b)从CDN传输数据的网络使用,(c)观察延迟,(d)CDN成本。我们还建议从源/ CDN服务器获取较高的比特率版本视频,并在飞行中将其转码到所请求的版本,以有效地使用自适应比特率(ABR)流和在线转码。该联合缓存和处理方法被制定为最小化问题,但经过存储,处理和带宽约束。我们还提出了一种在线贪婪算法,用于控制视频转码,使用X2或回程链路共享,并管理视频缓存并在边缘缓存中删除。仿真结果可以在不同配置的成本,平均延迟,缓存删除和缓存命中率方面,仿真算法更好地表现了我们所提出的算法。

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