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首页> 外文期刊>Journal of network and computer applications >Collaborative hierarchical caching and transcoding in edge network with CE-D2D communication
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Collaborative hierarchical caching and transcoding in edge network with CE-D2D communication

机译:具有CE-D2D通信边缘网络的协作分层缓存和转码

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To support multimedia applications, Mobile Edge Computing (MEC) servers offer storage and computing ca-pacities to handle videos close to end-users. However, the high load in peak hours consumes the limited available bandwidth of existing cellular and backhaul links leading to low network performance. Hence, an elastic system model is required to maintain the high Quality of Experience (QoE) as the resource demands increase. Caching popular videos at mobile devices is considered a promising technique for content delivery. Yet, mobile users offer small capacities that are not adequate for large-sized video sharing. In this paper, we extend the collaborative caching and processing framework in edge networks (Collaborative Edge CE) to include the users' mobile video sharing (Device-to-Device D2D). We propose a caching strategy to cache only the chunks of videos to be watched and instead of offloading one video content by one edge node, helpers (MEC servers and users) will collaborate to store and share different chunks to optimize the storage/transmission resources usage. To only cache popular contents, we designed a D2D-aware proactive chunks caching on users' devices based on our chunks popularity model. Next, we formulate this CE-D2D collaborative problem as a linear program. Due to the NP-hardness of the problem, we introduce a sub-optimal relaxation and an online heuristic using the proactive caching and presenting a near optimal data offloading and a profitable payment determination, with polynomial time complexity. The simulation results show that our policies and heuristics outperform other edge caching approaches by more than 10% in terms of hit ratio, average delay, and cost.
机译:为了支持多媒体应用,移动边缘计算(MEC)服务器提供存储和计算CA-Pacities,以处理靠近最终用户的视频。然而,高峰时段的高负荷消耗了现有蜂窝和回程链路的有限可用带宽,导致网络性能低。因此,随着资源需求的增加,需要弹性系统模型来维持高质量的经验(QoE)。移动设备上的热门视频被认为是用于内容交付的有希望的技术。然而,移动用户提供的小容量不适用于大型视频共享。在本文中,我们将协作缓存和处理框架扩展到边缘网络(协作边缘CE)以包括用户的移动视频共享(设备到设备D2D)。我们提出了一种缓存策略来缓存只能观看的视频块,而不是通过一个边缘节点卸下一个视频内容,而不是将一个视频内容卸下一个边缘节点,帮助器(MEC服务器和用户)将协作以存储和共享不同的块以优化存储/传输资源使用。只要缓存流行的内容,我们就设计了一个基于我们的块的人气模型的用户设备上的D2D感知主动块。接下来,我们将该CE-D2D协作问题作为线性程序制定。由于问题的NP - 硬度,我们使用主动缓存和呈现近最佳数据卸载和有利可图的支付确定,引入了次优的放松和在线启发式,以及多项式时间复杂性。仿真结果表明,在命中率,平均延迟和成本方面,我们的政策和启发式胜过了10%以上的其他边缘缓存方法。

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