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Fuzzy Decision Based Energy-Evolutionary System for Sustainable Transport in Ubiquitous Fog Network

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F23%3A10253185" target="_blank" >RIV/61989100:27240/23:10253185 - isvavai.cz</a>

  • Result on the web

    <a href="http://hcisj.com/data/file/article/2023070005/13-34.pdf?ckattempt=1" target="_blank" >http://hcisj.com/data/file/article/2023070005/13-34.pdf?ckattempt=1</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.22967/HCIS.2023.13.034" target="_blank" >10.22967/HCIS.2023.13.034</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Fuzzy Decision Based Energy-Evolutionary System for Sustainable Transport in Ubiquitous Fog Network

  • Original language description

    These days, the usage of sustainable transport applications has been growing in practice and has minimized global environmental issues as fuel vehicles did. Sustainable transport applications are distributed and can access data from anywhere in the network. However, due to sustainable electrical transport, much digital data is offloaded to the server to obtain the electricity stations. Therefore, many factors challenge sustainable vehicle applications, such as battery power consumption, service searching cost, execution delay, and execution accuracy. Thus, the existing decision support methods, such as TOPSIS multi-criteria decision method (MCDM), only support the fixed and accurate. Therefore, the fuzzy-based strategy will be more optimal for sustainable transport. The study devises the fuzzy-based energy-efficient decision support system (FBEES), which minimizes energy consumption, delay, and cost and increases scheduling accuracy for sustainable applications. These vehicles are connecting to the ubiquitous fog servers at different data centers in the system and offload their data for their processing. Simulation results show that FBEES minimizes energy by 30%, cost by 29%, delay by 31%, and improves accuracy compared to existing methods for sustainable transport applications. (C) This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    20200 - Electrical engineering, Electronic engineering, Information engineering

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2023

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Human-centric Computing and Information Sciences

  • ISSN

    2192-1962

  • e-ISSN

    2192-1962

  • Volume of the periodical

    13

  • Issue of the periodical within the volume

    2023

  • Country of publishing house

    KR - KOREA, REPUBLIC OF

  • Number of pages

    16

  • Pages from-to

  • UT code for WoS article

    001093214300001

  • EID of the result in the Scopus database

    2-s2.0-85168553061