Multi-Attribute Decision Making for Energy-Efficient Public Transport Network Selection in Smart Cities

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aut.relation.endpage42
aut.relation.issue2en_NZ
aut.relation.journalFuture Interneten_NZ
aut.relation.startpage42
aut.relation.volume14en_NZ
aut.researcherGutierrez, Jairo
dc.contributor.authorMunjal, Ren_NZ
dc.contributor.authorLiu, Wen_NZ
dc.contributor.authorLi, Xen_NZ
dc.contributor.authorGutierrez, Jen_NZ
dc.contributor.authorChong, PHJen_NZ
dc.date.accessioned2022-02-16T03:31:41Z
dc.date.available2022-02-16T03:31:41Z
dc.description.abstractSmart cities use many smart devices to facilitate the well-being of society by different means. However, these smart devices create great challenges, such as energy consumption and carbon emissions. The proposed research lies in communication technologies to deal with big data-driven applications. Aiming at multiple sources of big data in a smart city, we propose a public transport-assisted data-dissemination system to utilize public transport as another communication medium, along with other networks, with the help of software-defined technology. Our main objective is to minimize energy consumption with the maximum delivery of data. A multi-attribute decision-making strategy is adopted for the selction of the best network among wired, wireless, and public transport networks, based upon users’ requirements and different services. Once public transport is selected as the best network, the Capacitated Vehicle Routing Problem (CVRP) will be implemented to offload data onto buses as per the maximum capacity of buses. For validation, the case of Auckland Transport is used to offload data onto buses for energy-efficient delay-tolerant data transmission. Experimental results show that buses can be utilized efficiently to deliver data as per their demands and consume 33% less energy in comparison to other networks.en_NZ
dc.identifier.citationFuture Internet, 14(2), 42. https://doi.org/10.3390/fi14020042
dc.identifier.doi10.3390/fi14020042en_NZ
dc.identifier.issn1999-5903en_NZ
dc.identifier.urihttps://hdl.handle.net/10292/14911
dc.languageenen_NZ
dc.publisherMDPI AGen_NZ
dc.relation.urihttps://www.mdpi.com/1999-5903/14/2/42
dc.rights© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).
dc.rights.accessrightsOpenAccessen_NZ
dc.subjectBig data; Delay-tolerant network (DTN); Multi-attribute decision making; Public transport; Energy consumption
dc.titleMulti-Attribute Decision Making for Energy-Efficient Public Transport Network Selection in Smart Citiesen_NZ
dc.typeJournal Article
pubs.elements-id448494
pubs.organisational-data/AUT
pubs.organisational-data/AUT/Faculty of Design & Creative Technologies
pubs.organisational-data/AUT/Faculty of Design & Creative Technologies/School of Engineering, Computer & Mathematical Sciences
pubs.organisational-data/AUT/Faculty of Design & Creative Technologies/School of Engineering, Computer & Mathematical Sciences/Centre for Signals & Systems
pubs.organisational-data/AUT/Faculty of Design & Creative Technologies/School of Engineering, Computer & Mathematical Sciences/Network Security Research Group
pubs.organisational-data/AUT/PBRF
pubs.organisational-data/AUT/PBRF/PBRF Design and Creative Technologies
pubs.organisational-data/AUT/PBRF/PBRF Design and Creative Technologies/PBRF ECMS
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