Assessment of the Suitability of Fog Computing in the Context of Internet of Things

By Subhadeep Sarkar, Subarna Chatterjee, Sudip Misra. IEEE Transactions on Cloud Computing, 2018

615 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Information Systems

View Paper: https://www.semanticscholar.org/paper/d9c34e981037c8477cfd8b73470abace91ede3da

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Citations in the corpus

Survey of Fog Computing: Fundamental, Network Applications, and Research Challenges (2018, methodology): “[53] discussed the advantages of DC’s power consumption and reduced service latency in fog computing compared to traditional cloud computing.”
Smart Transportation: An Overview of Technologies and Applications (2023, background): “The Fog computing approach may be a preferable option for creating distributed applications [24] since it distributes computer resources closer to people and things, especially for latency-sensitive applications like Smart Transportation apps [25].”
Potentials, trends, and prospects in edge technologies: Fog, cloudlet, mobile edge, and micro data centers (2018, methodology): “presented mathematical model for fog computing paradigm by mathmatically quantifying power consumption, service latency, CO 2 mission, and computational cost [66] .”
Securing Fog Computing for Internet of Things Applications: Challenges and Solutions (2018, background): “[19] assessed the suitability of fog computing by characterizing power consumption, service latency,”
iFogSim: A toolkit for modeling and simulation of resource management techniques in the Internet of Things, Edge and Fog computing environments (2016, methodology): “[25] have performed a rigorous analysis comparing the performance of fog and cloud computing paradigms in the context of the Internet of Things by mathematically formulating the parameters and characteristics of fog computing.”
Edge-computing-driven Internet of Things: A Survey (2022, background): “showed the parameters and features of edge computing by mathematical calculations [155].”
Joint Computation and Communication Design for UAV-Assisted Mobile Edge Computing in IoT (2019, background): “e, locating MEC servers at a wireless access point (AP) or base station), it can efficiently reduce the delay and save the computation resource at these devices by the way of computation task offloading [3] [4].”
From Cloud to Fog Computing: A Review and a Conceptual Live VM Migration Framework (2017, background): “[29] described a three-tier architecture where the bottom tier comprises several terminal nodes (TN) (e.”
Resource aware placement of IoT application modules in Fog-Cloud Computing Paradigm (2017, background): “The ongoing work ranges from defining the architecture [4] to assessing its suitability in the context of IoT [5].”
A Comprehensive Survey on Fog Computing: State-of-the-Art and Research Challenges (2017, background): “[105], [106] consider in particular the performance of the fog systems in the context of IoT.”
Review of Internet of Things (IoT) in Electric Power and Energy Systems (2018, methodology): “Additionally, IoT ecosystems are constrained in terms of low power communications, scarce energy, and lossy communications, which necessitates localized computation and storage solutions for processing, analyzing, and storing IoT data [141]–[145].”
Fog Computing: A Taxonomy, Survey and Future Directions (2016, methodology): “In this sense, Fog computing better meets the requirements with respect to IoT applications compared to a solely use of Cloud computing [4].”
On Reducing IoT Service Delay via Fog Offloading (2018, background): “More recent work in [12] focuses on theoretical modeling of fog computing architectures, specifically, service delay, power consumption, and cost.”
Security and Privacy in Fog Computing: Challenges (2017, background): “1 illustrates the three-tier architecture [14], one of the basic and widely used architectures in fog computing.”
An Overview of Service Placement Problem in Fog and Edge Computing (2020, background): “There are several surveys that address diﬀerent aspects of Fog Computing and the related challenges [25, 30, 38, 41, 74, 82, 91, 95, 106, 117, 120, 123, 142, 158, 160].”
All One Needs to Know about Fog Computing and Related Edge Computing Paradigms: A Complete Survey (2018, background): “A three-layer general logical architecture for fog computing is introduced in [88] and [89].”
Incentive Mechanism Design for Computation Offloading in Heterogeneous Fog Computing: A Contract-Based Approach (2018, background): “It deploys cloud computing resources closely to users and have advantages of reducing transmission latency [5][7], minimizing energy consumption [6]-[8], alleviating computation burden [6][10] and improve social welfare [9].”
Cognitive computation and communication: A complement solution to cloud for IoT (2016, background): “The recent work in [7] shows that in the context of IoT with a high number of latency-sensitive applications Fog computing outperforms traditional cloud computing paradigms.”