城域网络中动态内容传递的缓存放置策略

Omran Ayoub, F. Musumeci, C. Addeo, M. Mussini, M. Tornatore
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引用次数: 2

摘要

视频点播(VoD)流量爆炸是最近互联网从传统的以连接为中心的架构向新的以内容为中心的范式演变的主要驱动力之一。为了应对这种演变,在核心、城域甚至城域接入光网络设备中缓存距离用户更近的VoD内容被认为是有助于缓解这种流量增长的主要解决方案。然而,最佳缓存位置和尺寸并不是唯一的,特别是在动态网络的上下文中,因为它取决于各种参数,例如网络拓扑、用户行为和内容流行度。在本文中,我们关注城域网中实现不同缓存策略的动态VoD内容交付场景。我们根据网络容量占用来评估各种缓存策略的性能,显示每个网段中节省的资源占用。我们还评估了存储容量的分布对所有请求的总体平均跳数的影响。得到的数值结果表明,通常,通过在终端用户附近启用内容缓存可以节省大量的网络资源。此外,我们还表明,盲目地在接入节点中提供缓存功能可能会导致不必要的结果,而在接入和城域网段之间均衡的存储分配可以提供最佳性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Caching Placement Strategies for Dynamic Content Delivery in Metro Area Networks
Video-on-Demand (VoD) traffic explosion has been one of the main driving forces behind the recent Internet evolution from a traditional connection-centric architecture towards the new content-centric paradigm. To cope with this evolution, caching of VoD contents closer to the users in core, metro and even metro-access optical network equipment is regarded to be a prime solution that could help mitigating this traffic growth. However, the optimal caches placement and dimensioning is not univocal, especially in the context of a dynamic network, as it depends on various parameters, such as network topology, users behavior and content popularity. In this paper, we focus on a dynamic VoD content delivery scenario in a metropolitan network implementing different caching strategies. We evaluate the performance of the various caching strategies in terms of network-capacity occupation showing the savings in resource occupation in each of the network segments. We also evaluate the effect of the distribution of the storage capacity on the overall average number of hops of all requests. The obtained numerical results show that, in general, a significant amount of network resources can be saved by enabling content caching near to end-users. Moreover, we show that blindly providing caching capability in access nodes may result unnecessary, whereas a balanced storage distribution between access and metro network segments provides the best performance.
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