While the success of edge and fog computing increased with the proliferation of the Internet of Things (IoT) solutions, such novel computing paradigm, that moves compute resources closer to the source of data and services, must address many challenges such as reducing communication overhead to/from datacenters, the latency to compute and receive results, as well as energy consumption at the mobile and IoT devices. fog-to-fog (f2f) cooperation has recently been proposed to increase the computation capacity at the network edge through cooperation across multiple stakeholders. In this paper we adopt an analytical approach to studying f2f cooperation paradigm. We highlight the benefits of using such new paradigm in comparison with traditional three-tier fog computing paradigms. We use a Continuous Time Markov Chain (CTMC) model for the N f2f cooperating nodes and cast cooperation as an optimization problem, which we solve using the proposed model.

翻译：尽管随着物联网解决方案的普及，边缘计算与雾计算取得了成功，但这种将计算资源向数据和服务源迁移的新型计算范式仍需应对诸多挑战，包括降低与数据中心之间的通信开销、缩短计算与获取结果的延迟，以及减少移动和物联网设备的能耗。近期提出的雾间协作旨在通过多利益相关方合作提升网络边缘的计算能力。本文采用分析方法研究雾间协作范式，重点阐述了相较于传统三层雾计算范式的优势。我们针对N个雾间协作节点构建了连续时间马尔可夫链模型，将协作问题转化为优化问题，并通过所提模型进行求解。