Fog Computing: A Taxonomy, Survey and Future Directions
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In this paper, the challenges in fog computing acting as an intermediate layer between IoT devices/sensors and cloud datacentres and review the current developments in this field are discussed.Abstract:
In recent years, the number of Internet of Things (IoT) devices/sensors has increased to a great extent. To support the computational demand of real-time latency-sensitive applications of largely geo-distributed IoT devices/sensors, a new computing paradigm named "Fog computing" has been introduced. Generally, Fog computing resides closer to the IoT devices/sensors and extends the Cloud-based computing, storage and networking facilities. In this chapter, we comprehensively analyse the challenges in Fogs acting as an intermediate layer between IoT devices/ sensors and Cloud datacentres and review the current developments in this field. We present a taxonomy of Fog computing according to the identified challenges and its key features.We also map the existing works to the taxonomy in order to identify current research gaps in the area of Fog computing. Moreover, based on the observations, we propose future directions for research.read more
Citations
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BookDOI
Service-oriented computing : ICSOC 2019 workshops : WESOACS, ASOCA, ISYCC, TBCE, and STRAPS, Toulouse, France, October 28-31, 2019, revised selected papers
Sami Yangui,Athman Bouguettaya,Xiao Xue,Noura Faci,Walid Gaaloul,Yu Qiu,Zhangbing Zhou,Nathalie Hernandez,Elisa Yumi Nakagawa +8 more
TL;DR: This paper presents initial experiments that were conducted with real use cases pertaining to Industry 4.0 and discusses a set of requirements that should be met by pervasive platforms to better support AIbased applications running in the edge.
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Predictive Method for Service Composition in Heterogeneous Environments within Client Requirements
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Proceedings ArticleDOI
A Discrete Cuckoo Search Algorithm for Reliability-aware Energy-efficient IoT Applications Multi-service Deployment in Fog Environment
TL;DR: A cuckoo search based algorithm is extended to avoid one point of failure phenomenon and to improve applications’ reliability and the results prove that the proposal significantly decreases total power consumption while it meets high level of reliability requested for IoT applications in comparison with other comparative state-of-the-arts.
Journal ArticleDOI
Collective Intelligence in Self-Organized Industrial Cyber-Physical Systems
TL;DR: The research indicates some potential benefits of using collective intelligence to achieve the desired levels of autonomy and dynamic adaptation of industrial CPS, but such approaches are still in the early stages, with perspectives to increase in the coming years.
Proceedings ArticleDOI
Distributed Deep Neural Networks with System Cost Minimization in Fog Networks
TL;DR: An efficient network resource allocation in neural networks over hybrid computing hierarchies, consisting of the cloud, the fog and end devices (hybrid-fog networks, H-FogN), is proposed.
References
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TL;DR: The definition of edge computing is introduced, followed by several case studies, ranging from cloud offloading to smart home and city, as well as collaborative edge to materialize the concept of edge Computing.
Proceedings ArticleDOI
Fog computing and its role in the internet of things
TL;DR: This paper argues that the above characteristics make the Fog the appropriate platform for a number of critical Internet of Things services and applications, namely, Connected Vehicle, Smart Grid, Smart Cities, and, in general, Wireless Sensors and Actuators Networks (WSANs).
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Fog Computing and Its Role in the Internet of Things
TL;DR: This chapter argues that the above characteristics make the Fog the appropriate platform for a number of critical internet of things services and applications, namely connected vehicle, smart grid, smart cities, and in general, wireless sensors and actuators networks (WSANs).
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iFogSim: A toolkit for modeling and simulation of resource management techniques in the Internet of Things, Edge and Fog computing environments
TL;DR: In this paper, the authors propose a simulator, called iFogSim, to model IoT and fog environments and measure the impact of resource management techniques in latency, network congestion, energy consumption, and cost.
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Edge-centric Computing: Vision and Challenges
Pedro García López,Alberto Montresor,Dick Epema,Anwitaman Datta,Teruo Higashino,Adriana Iamnitchi,Marinho P. Barcellos,Pascal Felber,Etienne Rivière +8 more
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