Fog and cloud load balancing using regression based recurrent deep learning algorithm

dc.contributor.advisorIbrahim, Abdullahi Abdu
dc.contributor.authorJameel, Eftekhar Jumaah
dc.date.accessioned2023-07-21T08:53:33Z
dc.date.available2023-07-21T08:53:33Z
dc.date.issued2022en_US
dc.date.submitted2022
dc.departmentEnstitüler, Lisansüstü Eğitim Enstitüsü, Elektrik ve Bilgisayar Mühendisliği Ana Bilim Dalıen_US
dc.description.abstractFog computing has been studied by a variety of academics, and they have identified concerns which need to be solved. It is the primary goal of this project to build and execute an energy conscious load balancer that will reduce energy usage and help in the distribution of loads. Furthermore, with chips becoming more compact and containing increasingly dense circuitry, the release of energy in the form of heat increases. This means even more energy consumption, as computational components do not operate well at very high temperatures and therefore are cooling systems. In this work we investigate the relative strengths and weaknesses of the different fog and cloud models and structures.en_US
dc.identifier.citationJameel, Eftekhar Jumaah. (2022). Fog and cloud load balancing using regression based recurrent deep learning algorithm. (Yayınlanmamış yüksek lisans tezi). Altınbaş Üniversitesi, Lisansüstü Eğitim Enstitüsü, İstanbul.en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12939/3577
dc.identifier.yoktezid746346
dc.institutionauthorJameel, Eftekhar Jumaah
dc.language.isoen
dc.publisherAltınbaş Üniversitesi / Lisansüstü Eğitim Enstitüsüen_US
dc.relation.publicationcategoryTezen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectFogen_US
dc.subjectClouden_US
dc.subjectMachine Learningen_US
dc.subjectArtificial Intelligenceen_US
dc.subjectGenetic Algorithmen_US
dc.titleFog and cloud load balancing using regression based recurrent deep learning algorithm
dc.typeMaster Thesis

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