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https://idr.l3.nitk.ac.in/jspui/handle/123456789/15117
Title: | Virtual Machine Migration in Heterogeneous Clouds - A Practical Approach |
Authors: | Raj S. Mangal N. Devi S. Salvi S.S. |
Issue Date: | 2020 |
Citation: | Proceedings of CONECCT 2020 - 6th IEEE International Conference on Electronics, Computing and Communication Technologies , Vol. , , p. - |
Abstract: | In modern times, Cloud Computing is viewed as more promising technology than any other traditional Information Technology Computing paradigms. It basically serves as an on-demand resource provisioning platform without any active intervention by its user. The resource provisioning strategies require appropriate load distribution management across the cloud network, without which the cloud would face biased workload performance. Virtualization is the backbone of Cloud Computing, which enables the distribution and management of data by initiating the Virtual Machines (VMs). Furthermore, a Cloud Service Provider(CSP) has to monitor, analyze, and manage the workload distribution for servers when VMs are migrated. It presents the need to consider VM migration as an important activity that would unload the cloud server that is overloaded to migrate it to the server that can handle the workload. This paper proposes a technique that initiates the migration of VMs between heterogeneous cloud environments that would lead to a stable and well-balanced cloud network. The process of VM migration is very intensive in terms of resources, and hence intelligent approaches are required. It should effectively reduce the utilization of network bandwidth by minimizing the downtime of the server. However, the migration of VMs between the heterogeneous cloud would be challenging, but the right solution would benefit the cloud network managers on a large scale. Our proposed technique demonstrates heterogeneous VM migration between various cloud platforms built on different architectures. Various parameters have to be technically tuned for the conversion of VM images according to the Cloud Architecture. The performance of the proposed technique is evaluated based on the time taken for migration. © 2020 IEEE. |
URI: | https://doi.org/10.1109/CONECCT50063.2020.9198551 http://idr.nitk.ac.in/jspui/handle/123456789/15117 |
Appears in Collections: | 2. Conference Papers |
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