网络边缘协作式泛在雾计算生态系统的一种范式
A Paradigm For Collaborative Pervasive Fog Computing Ecosystems at the Network Edge
AI总结：
本文研究网络边缘的雾到雾（f2f）合作范式，通过连续时间马尔可夫链模型将多节点合作转化为优化问题，证明其优于传统三层雾计算。
摘要：
尽管边缘和雾计算的成功随着物联网解决方案的普及而增加，但这种将计算资源移近数据和服务源的新型计算范式必须应对诸多挑战，如降低去往/来自数据中心的通信开销、计算和接收结果的延迟，以及移动和物联网设备的能耗。雾到雾（f2f）合作最近被提出，旨在通过跨多个利益相关者的合作来提高网络边缘的计算能力。在本文中，我们采用分析方法研究f2f合作范式。我们强调了与传统三层雾计算范式相比，使用这种新范式的优势。我们为N个f2f合作节点建立连续时间马尔可夫链（CTMC）模型，并将合作转化为优化问题，利用所提模型进行求解。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
