Journal ArticleDOI
Fog Computing: Helping the Internet of Things Realize Its Potential
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.read more
Citations
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Journal ArticleDOI
Managing Data Replication and Distribution in the Fog with FReD
TL;DR: FReD as discussed by the authors is a data replication middleware for the fog, which serves as a building block for configurable fog data distribution and enables low-latency, high-bandwidth, and privacy-sensitive applications.
Journal ArticleDOI
From cloud computing to fog computing in Healthcare big data
Babur Hayat Malik,Faisal Mahmood,Sohail Shahzad,Muhammad Bilawal Arif,Waseem Ur Rehman Khan,Sadaf Ilyas,Muhammad Umair Hassan +6 more
TL;DR: The impact of cloud computing and fog computing on healthcare big data, cloud base framework for Homediagnosis Service, Fog computing architecture and the justification of moving from cloud to Fog are presented comprehensively in this paper.
Book ChapterDOI
Energy Aware Task Consolidation in Fog Computing Environment
Satyabrata Rout,Sudhansu Shekhar Patra,Jnyana Ranjan Mohanty,Rabindra K. Barik,Rakesh Kumar Lenka +4 more
TL;DR: In this paper, the authors proposed a task consolidation for energy saving by reducing the unused nDCs in a fog computing environment and maximizing CPU utilization, which is a difficult NP-hard problem.
Journal Article
Fog computing: A review and conceptual architecture, issues, applications and its challenges
TL;DR: The fog computing architecture is described and its different services and applications are reviewed, and security and privacy issues in fog computing are discussed, focusing on service and resource availability.
Journal ArticleDOI
A survey on computation resource allocation in IoT enabled vehicular edge computing
Naren,Abhishek Kumar Gaurav,Nishad Sahu,Abhinash Prasad Dash,G. S. S. Chalapathi,Vinay Chamola +5 more
TL;DR: State-of-the-art computation resource allocation schemes are classified based on three criteria: (1) Their optimization goal, (2) Mathematical models/algorithms used, and (3) Major technologies involved.
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
Weisong Shi,Schahram Dustdar +1 more
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
Ivan Stojmenovic,Sheng Wen +1 more
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.