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

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20200 - Electrical engineering, Electronic engineering, Information engineering

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2023

Kód důvěrnosti údajů

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

Název periodika

Human-centric Computing and Information Sciences

ISSN

2192-1962

e-ISSN

2192-1962

Svazek periodika

13

Číslo periodika v rámci svazku

2023

Stát vydavatele periodika

KR - Korejská republika

Počet stran výsledku

16

Strana od-do

—

Kód UT WoS článku

001093214300001

EID výsledku v databázi Scopus

2-s2.0-85168553061