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dc.contributor.authorAkintoye, Samson Busuyi
dc.contributor.authorBagula, Antoine
dc.date.accessioned2021-12-06T11:49:23Z
dc.date.available2021-12-06T11:49:23Z
dc.date.issued2019
dc.identifier.citationAkintoye, S. B., & Bagula, A. (2019). Improving quality-of-service in cloud/fog computing through efficient resource allocation. Sensors, 19(6), 1267, 10.3390/s19061267en_US
dc.identifier.issn1424-8220
dc.identifier.urihttps://doi.org/10.3390/s19061267
dc.identifier.urihttp://hdl.handle.net/10566/7058
dc.description.abstractRecently, a massive migration of enterprise applications to the cloud has been recorded in the IT world. One of the challenges of cloud computing is Quality-of-Service management, which includes the adoption of appropriate methods for allocating cloud-user applications to virtual resources, and virtual resources to the physical resources. The effective allocation of resources in cloud data centers is also one of the vital optimization problems in cloud computing, particularly when the cloud service infrastructures are built by lightweight computing devices. In this paper, we formulate and present the task allocation and virtual machine placement problems in a single cloud/fog computing environment, and propose a task allocation algorithmic solution and a Genetic Algorithm Based Virtual Machine Placement as solutions for the task allocation and virtual machine placement problem models. Finally, the experiments are carried out and the results show that the proposed solutions improve Quality-of-Service in the cloud/fog computing environment in terms of the allocation cost.en_US
dc.language.isoenen_US
dc.publisherMPDIen_US
dc.subjectCloudSimen_US
dc.subjectVirtual machineen_US
dc.subjectCloud computingen_US
dc.subjectFog computingen_US
dc.subjectData centeren_US
dc.titleImproving quality-of-service in cloud/fog computing through efficient resource allocationen_US
dc.typeArticleen_US


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