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
Cloud-Fog Assisted Energy Efficient Architectural Paradigm for Disaster Evacuation
TL;DR: In this paper , an IoT based Cloud-Fog assisted layered evacuation system is proposed for mass evacuation during emergency situation, which utilizes fog computing paradigm to evaluate the panic health state in real-time using fuzzy K-nearest neighbor (FK-NN) method.
Proceedings ArticleDOI
A Data Infrastructure for Managing Information Obtained from Ambient Assisted Living
TL;DR: A Data Infrastructure for Managing Information Obtained from Ambient Assient Living is presented, which provides the data flow starting in the data reading in the IoT devices and ending in the Cloud by crossing Fog Computing Layer.
Journal ArticleDOI
HE3: A hierarchical attribute based secure and efficient things-to-fog content sharing protocol
Shardha Porwal,Sangeeta Mittal +1 more
TL;DR: A content sharing protocol named Hierarchical Efficient Encryption at Edge (HE3) is worked out to implement the concept and is demonstrated to be highly efficient in terms of encryption and decryption time as compared to existing approaches.
Proceedings ArticleDOI
A Secure Lightweight Data Aggregation scheme for Cloud assisted IoT
TL;DR: A secure lightweight data aggregation scheme for cloud assisted IoT devices based on ElGamal encryption and identity-based signature scheme is proposed that prevents the possibility of injection of any kind of false data and keeps a check on data leakages.
Proceedings ArticleDOI
Semantics-Aware Virtual Machine Image Management in IaaS Clouds
TL;DR: Expelliarmus as mentioned in this paper is a VMI management system that helps to minimize storage, publish and retrieval overheads by modeling VMIs as semantic graphs to expedite the similarity computation between multiple VMIs.
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.