Improved performance and cost algorithm for scheduling IoT tasks in fog-cloud environment using gray wolf optimization algorithm

Basit Öğe Kaydı
dc.contributor.authorAlsamarai, Naseem Adnan
dc.contributor.authorUçan, Osman Nuri
dc.date.accessioned2024-03-30T09:08:51Z
dc.date.available2024-03-30T09:08:51Z
dc.date.issued2024en_US
dc.departmentEnstitüler, Lisansüstü Eğitim Enstitüsü, Elektrik ve Bilgisayar Mühendisliği Ana Bilim Dalıen_US
dc.description.abstractToday, the IoT has become a vital part of our lives because it has entered into the precise details of human life, like smart homes, healthcare, eldercare, vehicles, augmented reality, and industrial robotics. Cloud computing and fog computing give us services to process IoT tasks, and we are seeing a growth in the number of IoT devices every day. This massive increase needs huge amounts of resources to process it, and these vast resources need a lot of power to work because the fog and cloud are based on the term pay-per-use. We make to improve the performance and cost (PC) algorithm to give priority to the high-profit cost and to reduce energy consumption and Makespan; in this paper, we propose the performance and cost-gray wolf optimization (PC-GWO) algorithm, which is the combination of the PCA and GWO algorithms. The results of the trial reveal that the PC-GWO algorithm reduces the average overall energy usage by 12.17%, 11.57%, and 7.19%, and reduces the Makespan by 16.72%, 16.38%, and 14.107%, with the best average resource utilization enhanced by 13.2%, 12.05%, and 10.9% compared with the gray wolf optimization (GWO) algorithm, performance and cost algorithm (PCA), and Particle Swarm Optimization (PSO) algorithm.en_US
dc.identifier.citationAlsamarai, N. A., Uçan, O. N. (2024). Improved performance and cost algorithm for scheduling IoT tasks in fog-cloud environment using gray wolf optimization algorithm. Applied Sciences - Basel, 14(4). 10.3390/app14041670en_US
dc.identifier.issn2076-3417
dc.identifier.issue4en_US
dc.identifier.scopus2-s2.0-85192482067
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://hdl.handle.net/20.500.12939/4648
dc.identifier.volume14en_US
dc.identifier.wosWOS:001168242000001
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorAlsamarai, Naseem Adnan
dc.institutionauthorUçan, Osman Nuri
dc.language.isoen
dc.relation.ispartofApplied Sciences - Basel
dc.relation.isversionof10.3390/app14041670en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - İdari Personel ve Öğrencien_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectFog-cloud computingen_US
dc.subjectTask schedulingen_US
dc.subjectEnergy consumptionen_US
dc.subjectMakespanen_US
dc.subjectResource utilizationen_US
dc.subjectCost schedulingen_US
dc.titleImproved performance and cost algorithm for scheduling IoT tasks in fog-cloud environment using gray wolf optimization algorithm
dc.typeArticle

Dosyalar

Orijinal paket
Listeleniyor 1 - 1 / 1
Küçük Resim
İsim:
applsci-14-01670.pdf
Boyut:
1.98 MB
Biçim:
Adobe Portable Document Format
Açıklama:
Tam Metin / Full Text
İndir
Lisans paketi
Listeleniyor 1 - 1 / 1
[ X ]
İsim:
license.txt
Boyut:
1.44 KB
Biçim:
Item-specific license agreed upon to submission
Açıklama:
İndir

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu