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
Internet of Spatial Things: A New Reference Model With Insight Analysis
TL;DR: This paper draws an inspiration towards the perspective vision of the IoST, which is concerned with revise IoT with the spatial perspective, and the Io ST concept is argued by the presentation of its definition and architectural components.
Journal ArticleDOI
FogIoHT: A weighted majority game theory based energy-efficient delay-sensitive fog network for internet of health things
TL;DR: Simulation results demonstrate that the proposed fog computing based system reduces the average delay, average jitter and energy consumption by approximately 15%, 20% and 15% respectively than the existing cloud only health care system.
Journal ArticleDOI
Task scheduling approaches in fog computing: A systematic review
TL;DR: The task scheduling algorithms proposed by different researchers for the cloud‐fog environment, their advantages and disadvantages, and also various tools and issues regarding the scheduling methods and their restrictions were discussed.
Journal ArticleDOI
Decentralized Edge-to-Cloud Load Balancing: Service Placement for the Internet of Things
TL;DR: The proposed solution, EPOS Fog, introduces a decentralized multi-agent system for collective learning that utilizes edge-to-cloud nodes to jointly balance the input workload across the network and minimize the costs involved in service execution.
Journal ArticleDOI
A Framework for Analyzing Fog-Cloud Computing Cooperation Applied to Information Processing of UAVs
Milena F. Pinto,André L. M. Marcato,Aurelio G. Melo,Leonardo de Mello Honório,Cristina Urdiales +4 more
TL;DR: A mathematical model to analyze distribution-based UAVs topologies and a fog-cloud computing framework for large-scale mission and search operations is proposed and the tests have successfully predicted latency and other operational constraints, allowing the analysis of fog-com computing advantages over traditional cloud-computing architectures.
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.