Fog Computing: Platform and Applications

By Shanhe Yi, Zijiang Hao, Zhengrui Qin, Qun A. Li. IEEE Workshop on Hot Topics in Web Systems and Technologies, 2015

713 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/488fa2f0c69b0008f9b069290e6c534766c42210

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

In Computer Vision and Pattern Recognition

Citations in the corpus

FogBus: A Blockchain-based Lightweight Framework for Edge and Fog Computing (2018, background): “In another work Yi et al. [21] propose a comprehensive PaaS framework for integrated environment.”
Foundations and Evolution of Modern Computing Paradigms: Cloud, IoT, Edge, and Fog (2019, background): “Most of research works related to the topic refer to a three-layer architecture composed of Cloud, Fog, and IoT [31], [44], [47], [52], [54].”
A Survey on Network Methodologies for Real-Time Analytics of Massive IoT Data and Open Research Issues (2017, background): “[151] in which the response time was reduced”
Mobile Edge Computing: A Survey (2018, background): “There are some terms similar to MEC, such as MCC, local cloud, cloudlets, and fog computing [18].”
The Internet of Things, Fog and Cloud Continuum: Integration and Challenges (2018, background): “Fog computing adds computing layers between users and cloud, which can be also used to oﬄoad [18, 4]; applications can be developed to take take oﬄoading into consideration [141].”
Distributed Deep Neural Networks Over the Cloud, the Edge and End Devices (2017, background): “For example, in [11], a face recognition application shows a reduced response time is achieved when a smartphone’s photos are proceeded by the edge (fog) as opposed to the cloud.”
Computation Offloading Toward Edge Computing (2019, background): “The intelligent edge analytics takes advantage of low latency and prevents the influx of information to DCs, especially in the field of IoT [45], [46].”
Edge Computing: Vision and Challenges (2016, neutral): “Researchers built a proof-of-concept platform to run face recognition application in [20], and the”
All One Needs to Know about Fog Computing and Related Edge Computing Paradigms: A Complete Survey (2018, neutral): “Definitions & Standards [6, 66, 68, 70–77, 85, 87, 106–123]”
From Cloud to Fog Computing: A Review and a Conceptual Live VM Migration Framework (2017, background): “[53] identified fog computing that is close to the edge of the network as the solution as well as integrating all components in a unified platform to enable smart home applications with elastic resources.”
Fog Computing: Survey of Trends, Architectures, Requirements, and Research Directions (2018, background): “On the other hand, the rate of failure in the Fog is high because of wireless connectivity, decentralized management, and power failure [26], [28]–[30].”
5G network slicing using SDN and NFV- A survey of taxonomy, architectures and future challenges (2019, background): “ in Virutal Machines (VMs) potentially over standard servers enabled on Fog/Cloud Computing (CC) en-8 A.A. Barakabitze, A. Ahmad and R. Mijumbi et al. / Computer Networks 167 (2020) 106984 vironments [64,65] . These softwarization capabilities can be de- ployed at different network sites based on sp”
A Comprehensive Survey on Fog Computing: State-of-the-Art and Research Challenges (2017, background): “This potential has been unveiled through several use cases [4], [11], [15], [47] in the context of cyber-physical systems, smart grid, micro-grid decentralized smart grid, smart trafﬁc light and connected vehicle, and decentralized smart building control.”
Fog Computing and the Internet of Things: A Review (2018, background): “It integrates all different platforms and empowers smart home applications with flexible resources [14].”
A New Deep Learning-Based Food Recognition System for Dietary Assessment on An Edge Computing Service Infrastructure (2018, background): “Edge computing is a non-trivial extension of cloud computing from the core network to the edge network [20], [21], [22], [23], [24], [25], [26].”
QoE and power efficiency tradeoff for fog computing networks with fog node cooperation (2017, background): “For example, large-scale environmental monitoring systems can deploy computational intensive applications at the sensors and utilize the fog computing architecture to achieve instantaneous environment monitoring and fast hazard detection [3], [4].”
Survey on fog computing: architecture, key technologies, applications and open issues (2017, background): “Some works have discussed the problem of authentication and trust in the fog however none of them have given a holistic solution (Yi et al., 2015c).”