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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

hpFog: A FPGA-Based Fog Computing Platform

TL;DR: A versatile high performance FPGA-based Fog platform to accommodate the growth of Internet-of-Thing and has remote connectivity to allow customized circuitry of hosted applications to be software-defined by external management or development entity once deployed.
Journal ArticleDOI

An Improved Ant Colony Optimization Algorithm: A Technique for Extending Wireless Sensor Networks Lifetime Utilization

TL;DR: An improved ant colony optimization algorithm is used to construct optimal paths between the cluster heads and fog nodes for a reliable end-to-end data packets delivery and the network lifetime in AMACO increased.
Journal ArticleDOI

Security in fog computing: A systematic review on issues, challenges and solutions

TL;DR: In this paper, a comprehensive study of security challenges and different approaches in fog computing to address those challenges using the Systematic Literature Review (SLR) approach is presented, which analytically and statistically classify the existing research techniques related to security aspects and available solutions in fog Computing published between 2014 and 2021.
Proceedings ArticleDOI

Incentivizing Hosts via Multilateral Cooperation in User-Provided Networks: A Fluid Shapley Value Approach

TL;DR: A market of UPN is model, consisting of ISP, hosts, and clients via game theory, where various heterogeneities in terms of willingness to pay and mobility pattern of clients, hosts' QoS, and type of cooperation among ISP and hosts are modeled.
Journal ArticleDOI

Decentralized Application Placement in Fog Computing

TL;DR: In this article , the effects of decentralization and coordination on the optimization results of application placement in fog and edge computing are compared empirically, and it is shown that, for large problem instances, decentralization combined with coordination leads to the best results.
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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