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Soft Computing
Erschienen in: Soft Computing 21/2019

02.01.2019 | Methodologies and Application

Cloud computing-based resource provisioning using k-means clustering and GWO prioritization

verfasst von: A. Meenakshi, H. Sirmathi, J. Anitha Ruth

Erschienen in: Soft Computing | Ausgabe 21/2019

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Abstract

As the use of cloud computing continues to grow, issues related to cloud services such as resource allocation, security, virtual machine migration and quality of service (QoS) are also increasing. To overcome this, resource provisioning and stack adjusting were employed. In this paper, we suggest another approach that allocates resources with least waste and provides the greatest benefit. Here, the customer first submits a request for resources to the resource allocation manager, which forwards this request to the request tuner. It creates the charge and sends this to all resources connected in cloud system with the guide of grouping algorithm. After the GWO algorithm is applied for prioritization. The virtual machines are distributed for resources based on require therefore; the load on the server can be substantially reduced. In addition, allocating resources on virtual machines based on demand achieves a better response time and preparation time.
Vorheriger Artikel Experimental analysis of design elements of scalarizing function-based multiobjective evolutionary algorithms
Nächster Artikel Hybrid rough fuzzy soft classifier based multi-class classification model for agriculture crop selection

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Metadaten
Titel
Cloud computing-based resource provisioning using k-means clustering and GWO prioritization
verfasst von
A. Meenakshi
H. Sirmathi
J. Anitha Ruth
Publikationsdatum
02.01.2019
Verlag
Springer Berlin Heidelberg
Erschienen in
Soft Computing / Ausgabe 21/2019
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-018-3632-9

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