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Fog-Aided Wireless Networks for Content Delivery: Fundamental Latency Tradeoffs

机译：用于内容交付的雾辅助无线网络：基本延迟权衡

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A fog-aided wireless network architecture is studied in which edge nodes (ENs), such as base stations, are connected to a cloud processor via dedicated fronthaul links while also being endowed with caches. Cloud processing enables the centralized implementation of cooperative transmission strategies at the ENs, albeit at the cost of an increased latency due to fronthaul transfer. In contrast, the proactive caching of popular content at the ENs allows for the low-latency delivery of the cached files, but with generally limited opportunities for cooperative transmission among the ENs. The interplay between cloud processing and edge caching is addressed from an information-theoretic viewpoint by investigating the fundamental limits of a high signal-to-noise-ratio metric, termed normalized delivery time (NDT), which captures the worst case coding latency for delivering any requested content to the users. The NDT is defined under the assumptions of either serial or pipelined fronthaul-edge transmission, and is studied as a function of fronthaul and cache capacity constraints. Placement and delivery strategies across both fronthaul and wireless, or edge, segments are proposed with the aim of minimizing the NDT. Information-theoretic lower bounds on the NDT are also derived. Achievability arguments and lower bounds are leveraged to characterize the minimal NDT in a number of important special cases, including systems with no caching capabilities, as well as to prove that the proposed schemes achieve optimality within a constant multiplicative factor of 2 for all values of the problem parameters.
机译：研究了雾辅助无线网络架构，其中边缘节点（EN）（例如基站）通过专用的前传链路连接到云处理器，同时还拥有高速缓存。云处理可以在EN上集中实施协作传输策略，尽管这会因前传传输而导致延迟增加。相反，在EN处对流行内容进行主动缓存可以实现缓存文件的低延迟交付，但在EN之间进行协作传输的机会通常有限。从信息理论的角度，通过研究高信噪比指标的基本限制（称为归一化传送时间（NDT）），解决了云处理和边缘缓存之间的相互作用，该捕获标准捕获了传送的最坏情况下的编码延迟向用户请求的任何内容。 NDT是在串行或流水线前传边缘传输的假设下定义的，并根据前传和缓存容量约束进行研究。提出了跨前传和无线或边缘网段的放置和传送策略，目的是使NDT最小化。还推导了NDT的信息理论下限。在许多重要的特殊情况下，包括在没有缓存功能的系统中，都利用可达到性参数和下界来描述最小NDT的特征，并证明所提出的方案对于2的所有值在恒定乘数2内实现了最优性。问题参数。

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