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Latency-Driven Fog Cooperation Approach in Fog Radio Access Networks

机译：雾无线电接入网中的延迟驱动的雾合作方法

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摘要

Fog computing, evolves from the cloud and migrates the computing to the edge, is a promising solution to meet the increasing demand for ultra-low latency services in wireless networks. Via the forward-looking perspective, we advocate a ${Fog, Radio, Access}$FogRadioAccess ${Network, (Fhbox{-}RAN)}$Network(F-RAN) model, which leverages the existing infrastructure such as small cells with limited computing power, to achieve the ultra-low latency by joint edge computing and near-range communications across multiple Fog groups. We formulate the low latency design as an $mathcal {NP}$NP-hard optimization problem, which demonstrates the tradeoff between communication and computing in the time domain. Due to each F-RAN node's potential as each user's master F-RAN node with 1) different self computing power; and 2) different cooperative power of assisted F-RAN nodes, we first tackle globally optimized master F-RAN node selection for each user and propose a latency-driven cooperative Fog algorithm with dynamic programming solution for simultaneous selection of the F-RAN nodes to serve proper heterogeneous Fog resource allocation for multi-Fog groups. Considering the limited heterogeneous Fog resources shared among all users, we propose the one-for-all strategy for every user putting him/herself into others' shoes and reaching a "win-win" outcome. The numerical results show that the low latency services can be accomplished by F-RAN via latency-driven Fog cooperation approach.
机译：雾计算从云发展而来，并将计算迁移到边缘，是一种有前途的解决方案，可以满足对无线网络中超低延迟服务不断增长的需求。通过前瞻性的观点，我们提倡使用现有的$ {Fog ，Radio ，Access} $ FogRadioAccess $ {Network ，（F hbox {-} RAN）} $ Network（F-RAN）模型基础架构（例如具有有限计算能力的小型蜂窝），以通过联合边缘计算和跨多个Fog组的近距离通信来实现超低延迟。我们将低延迟设计公式化为$ mathcal {NP} $ NP困难的优化问题，这证明了时域中通信与计算之间的权衡。由于每个F-RAN节点作为每个用户的主F-RAN节点的潜力，具有1）不同的自计算能力；和2）辅助F-RAN节点的协作能力不同，我们首先针对每个用户解决全局优化的主F-RAN节点选择问题，然后提出一种具有动态编程解决方案的时延驱动的协作Fog算法，以便同时选择F-RAN节点以为多雾组提供适当的异构雾资源分配。考虑到所有用户之间共享的有限的异构Fog资源，我们为每个用户提出了“一对一”策略，将他/她自己置于他人的鞋子中，并实现了“双赢”的结果。数值结果表明，低时延服务可以由F-RAN通过时延驱动的Fog协作方法完成。

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