Fog of Everything: Energy-Efficient Networked Computing Architectures, Research Challenges, and a Case Study

By Enzo Baccarelli, Paola Gabriela Vinueza Naranjo, Michele Scarpiniti, Mohammad Shojafar, Jemal H. Abawajy. 2017

315 citations recorded by the source corpus.

Fog computing (FC) and Internet of Everything (IoE) are two emerging technological paradigms that, to date, have been considered standing-alone. However, because of their complementary features, we expect that their integration can foster a number of computing and network-intensive pervasive applications under the incoming realm of the future Internet. Motivated by this consideration, the goal of this position paper is fivefold. First, we review the technological attributes and platforms proposed in the current literature for the standing-alone FC and IoE paradigms. Second, by leveraging some use cases as illustrative examples, we point out that the integration of the FC and IoE paradigms may give rise to opportunities for new applications in the realms of the IoE, Smart City, Industry 4.0, and Big Data Streaming, while introducing new open issues. Third, we propose a novel technological paradigm, the Fog of Everything (FoE) paradigm, that integrates FC and IoE and then we detail the main building blocks and services of the corresponding technological platform and protocol stack. Fourth, as a proof-of-concept, we present the simulated energy-delay performance of a small-scale FoE prototype, namely, the V-FoE prototype. Afterward, we compare the obtained performance with the corresponding one of a benchmark technological platform, e.g., the V-D2D one. It exploits only device-to-device links to establish inter-thing “ad hoc” communication. Last, we point out the position of the proposed FoE paradigm over a spectrum of seemingly related recent research projects.

Subfields: Computer Networks and Communications, ML Systems & Hardware

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Citations in the corpus

Why Should We Add Early Exits to Neural Networks? (2020, background): “They also provide a viable entry point to the study of more biologically plausible alternatives to classical back-propagation, and they are more naturally suited to an implementation in multi-tiered computational frameworks such as the emerging fog computing one [2].”
Fog Computing: Survey of Trends, Architectures, Requirements, and Research Directions (2018, methodology): “…computing were also presented by various researchers including the hierarchical Fog architecture [60], [61], OpenFog architecture [62], Fog network architecture [63], Fog architecture for Internet of energy [9], Fog computing Architecture based on nervous system [64], and IFCIoT architecture [65].”
A Survey on Smart Agriculture: Development Modes, Technologies, and Security and Privacy Challenges (2021, background): “Due to the resource-limited sensors and bandwidth-limited wireless communication, the Fog of Everything (FoE) was proposed in [150] to set up a complexity system.”
Industry 4.0 for the Construction Industry—How Ready Is the Industry? (2019, background): “…the Context of Industry 4.0: A Triangulation Approach and Elements of a Research Agenda for the Construction Industry [32] 176 Computers in Industry Baccarelli et al. (2017) Fog of Everything: Energy-Efficient Networked Computing Architectures, Research Challenges, and a Case Study [40] 98 IEEE…”
Differentiable Branching In Deep Networks for Fast Inference (2020, background): “In addition, this class of ‘branching’ neural networks can be distributed across multiple tiers of distributed computing platforms, making them a perfect ﬁt for scenarios in Fog computing [13] and 5G [3,14].”