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


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.

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Correspondence to A. Meenakshi.

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Meenakshi, A., Sirmathi, H. & Anitha Ruth, J. Cloud computing-based resource provisioning using k-means clustering and GWO prioritization. Soft Comput 23, 10781–10791 (2019).

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  • Resource provisioning
  • Security
  • Virtual machine migration
  • Quality of services
  • Gray wolf optimization