Fog-based smart homes: A systematic review

Smart homes are equipped residences for clients aiming at supplying suitable services via intelligent technologies. Through smart homes, household appliances as the Internet of Things (IoT) devices can easily be handled and monitored from a far distance by remote controls. With the day-to-day popula...

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Bibliographic Details
Published in:Journal of network and computer applications 2020-03, Vol.153, p.102531, Article 102531
Main Authors: Rahimi, Morteza, Songhorabadi, Maryam, Kashani, Mostafa Haghi
Format: Article
Language:English
Subjects:
Fog computing
Internet of things (IoT)
Smart buildings
Smart homes
Systematic review
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Summary:Smart homes are equipped residences for clients aiming at supplying suitable services via intelligent technologies. Through smart homes, household appliances as the Internet of Things (IoT) devices can easily be handled and monitored from a far distance by remote controls. With the day-to-day popularity of smart homes, it is anticipated that the number of connections rises faster. With this remarkable rise in connections, some issues such as substantial data volumes, security weaknesses, and response time disorders are predicted. In order to solve these obstacles and suggest an auspicious solution, fog computing as an eminently distributed architecture has been proposed to administer the massive, security-crucial, and delay-sensitive data, which are produced by communications of the IoT devices in smart homes. Indeed, fog computing bridges space between various IoT appliances and cloud-side servers and brings the supply side (cloud layer) to the demand side (user device layer). By utilizing fog computing architecture in smart homes, the issues of traditional architectures can be solved. This paper proposes a Systematic Literature Review (SLR) method for fog-based smart homes (published between 2014 and May 2019). A practical taxonomy based on the contents of the present research studies is represented as resource-management-based and service-management-based approaches. This paper also demonstrates an abreast comparison of the aforementioned solutions and assesses them under the same evaluation factors. Applied tools, evaluation types, algorithm types, and the pros and cons of each reviewed paper are observed as well. Furthermore, future directions and open challenges are discussed.
ISSN:1084-8045
1095-8592
DOI:10.1016/j.jnca.2020.102531