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Fog Computing: A Taxonomy, Survey and Future Directions

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TLDR
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.

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Citations
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Journal ArticleDOI

A Survey on Energy Efficient Routing Techniques in WSNs Focusing IoT Applications and Enhancing Fog Computing Paradigm

TL;DR: This study examines the most recent routing protocols for sensor networks and introduces a new routing protocol to increase the energy efficiency of sensor devices in the Internet of Things.
Journal ArticleDOI

Mutual authentication with multi-factor in IoT-Fog-Cloud environment

TL;DR: This work aims to improve a method of mutual authentication with multi-factor using an adjustable variable response time, challenge-response function, and nonce, and demonstrates that it is impossible to derive the discovery of keys, keeping the proposed method safe.
Journal ArticleDOI

Secure and efficient data delivery for fog-assisted wireless body area networks

TL;DR: A secure and efficient data delivery protocol that will reduce delay and protect against malicious attacks on the wireless signal is proposed, which showed clear improvements in the efficiency and resiliency of the fog-assisted WBAN system when utilizing this protocol.
Proceedings ArticleDOI

Fog Computing Solution for Distributed Anomaly Detection in Smart Grids

TL;DR: Fog Computing model is proposed to detect the anomalous patterns in the electricity consumption data by means of collaboration of distributed devices at the edge of Smart Grid network enough in advance (reducing communication latencies).
Proceedings ArticleDOI

Privacy-preserving Schemes for Fog-based IoT Applications: Threat models, Solutions, and Challenges

TL;DR: A survey of existing privacy-preserving schemes for fog-based Internet of Things (IoT) applications, including, holistic privacy, privacy- Preserving aggregation, trajectory privacy, conditional privacy preservation, differential privacy, data privacy, user’s privacy, and location privacy, is presented.
References
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Journal ArticleDOI

Edge Computing: Vision and Challenges

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).
Book ChapterDOI

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).
Journal ArticleDOI

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.
Journal ArticleDOI

Edge-centric Computing: Vision and Challenges

TL;DR: This position paper position that a new shift is necessary in computing, taking the control of computing applications, data, and services away from some central nodes to the other logical extreme of the Internet, and refers to this vision of human-centered edge-device based computing as Edge-centric Computing.
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