Optimization planning techniques with meta-heuristic algorithms in IoT: performance and QoS evaluation

Basit Öğe Kaydı
dc.authoridhttps://orcid.org/0000-0002-6048-7645
dc.authoridhttps://orcid.org/0000-0001-7032-8018
dc.contributor.authorKoca, Murat
dc.contributor.authorAvcı, İsa
dc.date.accessioned2025-01-22T09:17:30Z
dc.date.available2025-01-22T09:17:30Z
dc.date.issued2024-08-31
dc.departmentFakülteler, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü
dc.description.abstractBig data analysis used by Internet of Things (IoT) objects is one of the most difficult issues to deal with today due to the data increase rate. Container technology is one of the many technologies available to address this problem. Because of its adaptability, portability, and scalability, it is particularly useful in IoT micro-services. The most promising lightweight virtualization method for providing cloud services has emerged owing to the variety of workloads and cloud resources. The scheduler component is critical in cloud container services for optimizing performance and lowering costs. Even though containers have gained enormous traction in cloud computing, very few thorough publications address container scheduling strategies. This work organizes its most innovative contribution around optimization scheduling techniques, which are based on three metaheuristic algorithms. These algorithms include the particle swarm algorithm, the genetic algorithm, and the ant colony algorithm. We examine the main advantages, drawbacks, and significant difficulties of the existing approaches based on performance indicators. In addition, we made a fair comparison of the employed algorithms by evaluating their performance through Quality of Service (QoS) while each algorithm proposed a contribution. Finally, it reveals a plethora of potential future research areas for maximizing the use of emergent container technology.
dc.description.sponsorshipSupporting Institution : Van Yuzuncu Yil University Scientific Research Projects Coordination Unit Project Number : FYD-2022-10337
dc.identifier10.35377/saucis...1452049
dc.identifier.citationKOCA, M., AVCI, İ. (2024). Optimization Planning Techniques with Meta-Heuristic Algorithms in IoT: Performance and QoS Evaluation. Sakarya University Journal of Computer and Information Sciences (Online), 7(2),173-186. doi.org/10.35377/saucis...1452049
dc.identifier.doi10.35377/saucis...1452049
dc.identifier.endpage186
dc.identifier.issn2636-8129
dc.identifier.issue2
dc.identifier.scopus2-s2.0-85214817120
dc.identifier.startpage173
dc.identifier.trdizinid1261208
dc.identifier.urihttps://doi.org/10.35377/saucis...1452049
dc.identifier.urihttps://hdl.handle.net/20.500.14619/15007
dc.identifier.volume7
dc.indekslendigikaynakScopus
dc.indekslendigikaynakTR-Dizin
dc.language.isoen
dc.publisherSakarya University
dc.relation.ispartofSakarya University Journal of Computer and Information Sciences
dc.relation.ispartofseriesSakarya University Journal of Computer and Information Sciences
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectContainer method
dc.subjectIoT micro-services
dc.subjectMetaheuristic algorithms
dc.subjectOptimization algorithms
dc.subjectScheduling methods
dc.titleOptimization planning techniques with meta-heuristic algorithms in IoT: performance and QoS evaluation
dc.typeArticle
oaire.citation.issue2
oaire.citation.volume7

Dosyalar

Lisans paketi
Listeleniyor 1 - 1 / 1
Küçük Resim Yok
İsim:
license.txt
Boyut:
1.17 KB
Biçim:
Item-specific license agreed upon to submission
Açıklama:
İndir

Koleksiyon

Mühendislik Fakültesi Koleksiyonu