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
Human Data Model: Improving Programmability of Health and Well-Being Data for Enhanced Perception and Interaction
Niko Mäkitalo,Daniel Flores-Martin,Huber Flores,Eemil Lagerspetz,Francois Christophe,Petri Ihantola,Masiar Babazadeh,Pan Hui,Juan Manuel Murillo,Sasu Tarkoma,Tommi Mikkonen +10 more
TL;DR: Today, an increasing number of systems produce, process, and store personal and intimate data, which has plenty of potential for entirely new types of software applications, as well as for impr...
Book ChapterDOI
Collaborative Mechanism for Hybrid Fog‐Cloud Scenarios
TL;DR: In this paper, the authors introduce the collaborative scenario paying special attention to the architectural models as well as to the challenges posed when considering the fog-cloud collaborative model enriched with new strategies such as innovative resource sharing.
Journal ArticleDOI
Privacy-Preserving Data Aggregation with Dynamic Billing in Fog-Based Smart Grid
TL;DR: Wang et al. as mentioned in this paper proposed a privacy-preserving data aggregation scheme that supports dynamic billing and arbitration, named PPDB, which uses fog nodes (FNs) to collect and aggregate electricity consumption data encrypted under the ElGamal cryptosystem and employ distributed decryption to achieve fine-grained access and bills generation based on real-time prices.
Proceedings ArticleDOI
Multi-Objective Service Provisioning in Fog: A Trade-Off Between Delay and Cost Using Goal Programming
TL;DR: A multi-objective framework to find eligible fog nodes to dynamically deploy the IoT applications on them and could be employed to achieve a trade-off between the cost of resources and average service delay is presented.
Journal ArticleDOI
Cost Efficient Edge Service Placement for Crowdsensing via Bus Passengers
TL;DR: This paper considers the MCS applications supported by the mobile phones of bus passengers, who transfer between different bus stations equipped with edge servers, and designs a low-complexity heuristic algorithm to seek a tradeoff between communication cost and service deployment cost to pursue overall cost efficiency.
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.