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Journal ArticleDOI

Fog Computing: Helping the Internet of Things Realize Its Potential

Amir Vahid Dastjerdi, +1 more
- 01 Aug 2016 - 
- Vol. 49, Iss: 8, pp 112-116
TLDR
Fog computing is designed to overcome limitations in traditional systems, the cloud, and even edge computing to handle the growing amount of data that is generated by the Internet of Things.
Abstract
The Internet of Things (IoT) could enable innovations that enhance the quality of life, but it generates unprecedented amounts of data that are difficult for traditional systems, the cloud, and even edge computing to handle. Fog computing is designed to overcome these limitations.

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Citations
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Proceedings ArticleDOI

Error correction method considering fog and edge computing environment

TL;DR: The proposed methods can solve the data congestion problems at a cloud in the future IoT era and use the locality of fog and edge.
Journal ArticleDOI

A comprehensive study on managing strategies in the fog environments

TL;DR: A detailed survey for covering the current state‐of‐the‐art in fog management, which classifies the management strategies into three main categories: data management, energy, and resource.
Proceedings ArticleDOI

Architecture for Internet of Things Environment Management with Quality of Service Assurance

TL;DR: The proposed dynamic and self-manageable architecture aims to relate mechanisms of prediction and load balancing, as well as access control, resources management and security, and ensures the Quality of Service (QoS).
Dissertation

Proposal of an adaptable and scalable IoT middleware for hybrid computational models

TL;DR: It is demonstrated that the proposal met its objectives, allowing the creation of IoT networks in heterogeneous scenarios, maintaining its functionalities and allowing its users have greater ownership and confidence in the data they handle on its IoT network.
Journal ArticleDOI

An Approach to the Unified Management of Heterogeneous IoT Environments

TL;DR: It is shown that the management of the heterogeneity of the sensing/actuating IoT devices is feasible, by presenting functionalities related to real use cases and comparing the performances of lightweight machine to machine (LwM2M) and ultralight device management services in FIWARE.
References
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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.
Book ChapterDOI

Fog Computing: A Platform for Internet of Things and Analytics

TL;DR: This chapter proposes a hierarchical distributed architecture that extends from the edge of the network to the core nicknamed Fog Computing, and pays attention to a new dimension that IoT adds to Big Data and Analytics: a massively distributed number of sources at the edge.
Journal ArticleDOI

The Promise of Edge Computing

TL;DR: The success of the Internet of Things and rich cloud services have helped create the need for edge computing, in which data processing occurs in part at the network edge, rather than completely in the cloud.
Proceedings ArticleDOI

The Fog computing paradigm: Scenarios and security issues

TL;DR: The motivation and advantages of Fog computing are elaborated, and its applications in a series of real scenarios, such as Smart Grid, smart traffic lights in vehicular networks and software defined networks are analysed.
Proceedings ArticleDOI

Towards wearable cognitive assistance

TL;DR: The architecture and prototype implementation of an assistive system based on Google Glass devices for users in cognitive decline that combines the first-person image capture and sensing capabilities of Glass with remote processing to perform real-time scene interpretation is described.
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