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
Survey on DDoS Attacks and Defense Mechanisms in Cloud and Fog Computing
TL;DR: How cloud computing has emerged as a strong competitor against traditional IT platforms by offering low-cost and “pay-as-you-go” computing potential and on-demand provisioning of services is described.
Journal ArticleDOI
Internet of things-inspired healthcare system for urine-based diabetes prediction.
TL;DR: Enhanced results in terms of temporal delay, classification efficiency, prediction efficiency, reliability and stability were registered for the proposed system in comparison to state-of-the-art decision-making techniques.
Journal ArticleDOI
Nano-networks communication architecture: Modeling and functions
Akram Galal,Xavier Hesselbach +1 more
TL;DR: An unified architectural model of Nano-network communication with a layered approach combining Software Defined Network (SDN), Network Function Virtualization (NFV) and IoT technologies is provided and how this combination can help in Nano-networks’ context is presented.
Journal ArticleDOI
Edge Computing to Secure IoT Data Ownership and Trade with the Ethereum Blockchain.
Anum Nawaz,Anum Nawaz,Jorge Peña Queralta,Jixin Guan,Muhammad Awais,Tuan Nguyen Gia,Ali Kashif Bashir,Haibin Kan,Tomi Westerlund +8 more
TL;DR: EdgeBoT, a proof-of-concept smart contracts based platform for the IoT built on top of the ethereum blockchain, enables a wider variety of interaction topologies between nodes in the network and external services while guaranteeing ownership of data and end users’ privacy.
Journal ArticleDOI
Remote Pain Monitoring Using Fog Computing for e-Healthcare: An Efficient Architecture.
TL;DR: The results of the simulations carried out in this research indicate that a reduction in both latency and network consumption can be achieved by adopting the proposed approach for implementing a remote pain monitoring system.
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.