Edge Computing for Internet of Things

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Dublin Core

Title

Edge Computing for Internet of Things

Subject

INTERNET
TECHNOLOGY

Description

The Internet-of-Things is becoming an established technology, with devices being deployed in homes, workplaces, and public areas at an increasingly rapid rate. IoT devices are the core technology of smart-homes, smart-cities, intelligent transport systems, and promise to optimise travel, reduce energy usage and improve quality of life. With the IoT prevalence, the problem of how to manage the vast volumes of data, wide variety and type of data generated, and erratic generation patterns is becoming increasingly clear and challenging. This Special Issue focuses on solving this problem through the use of edge computing. Edge computing offers a solution to managing IoT data through the processing of IoT data close to the location where the data is being generated. Edge computing allows computation to be performed locally, thus reducing the volume of data that needs to be transmitted to remote data centres and Cloud storage. It also allows decisions to be made locally without having to wait for Cloud servers to respond.

Creator

Lee, Kevin (editor)
Man, Ka Lok (editor)

Source

https://directory.doabooks.org/handle/20.500.12854/84496

Publisher

MDPI - Multidisciplinary Digital Publishing Institute

Date

2022

Contributor

SULISTIORINI

Rights

https://creativecommons.org/licenses/by/4.0/

Relation

Kevin Lee and Ka Lok Man
Edge Computing for Internet of Things
Reprinted from: Electronics 2022, 11, 1239, doi:10.3390/electronics11081239
Jorge Coelho and Lu´ıs Nogueira
Enabling Processing Power Scalability with Internet of Things (IoT) Clusters
Reprinted from: Electronics 2021, 11, 81, doi:10.3390/electronics11010081
Hong-Jun Jang, Yeongwook Yang, Ji Su Park and Byoungwook Kim
FP-Growth Algorithm for Discovering Region-Based Association Rule in the IoT Environment
Reprinted from: Electronics 2021, 10, 3091, doi:10.3390/electronics10243091
Kolade Olorunnife, Kevin Lee and Jonathan Kua
Automatic fault-tolerance for IoT devices in unreliable networks
Reprinted from: Electronics 2021, 10, 3047, doi:10.3390/electronics10233047 . . . . . . . . . . . . . 33
Svetlana Kim, Jieun Kang and YongIk Yoon
Linked-Object Dynamic Offloading (LODO) for the Cooperation of Data and Tasks on Edge
Computing Environment
Reprinted from: Electronics 2021, 10, 2156, doi:10.3390/electronics10172156
Mumraiz Khan Kasi, Sarah Abu Ghazalah, Raja Naeem Akram and Damien Sauveron
Secure Mobile Edge Server Placement Using Multi-Agent Reinforcement Learning
Reprinted from: Electronics 2021, 10, 2098, doi:10.3390/electronics10172098

Format

Pdf

Language

English

Type

Textbooks

Identifier

DOI
10.3390/books978-3-0365-4275-1
ISBN
9783036542768, 9783036542751

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