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：尽管边缘和雾计算随着物联网解决方案的普及而取得成功，但这种将计算资源移至数据和服务源附近的新型计算范式仍需应对诸多挑战，包括减少与数据中心之间的通信开销、降低计算与结果接收的延迟，以及移动和物联网设备的能耗。雾到雾（f2f）协作方案近期被提出，旨在通过多利益相关方协作提升网络边缘的计算能力。本文采用分析方法研究f2f协作范式，对比传统三级雾计算范式凸显该新范式的优势。我们针对N个f2f协作节点构建连续时间马尔可夫链（CTMC）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。