Year: 2018
Type: dissertation
Abstract: VMM (Virtual Machine Migration) is known as a dynamic management method that \nprovides the operators of data centres the ability to have VM placement for satisfying the performance objectives, enhance communication locality with resource utilization, mitigation of performance hotspots, lessening energy consumption, to have fault tolerance. The effective VMM (Virtual Machine Migration) technique is considered as a problem because it not merely needs weighing the VM migration benefits but also has migration cost with service disruption, management overhead and communication cost. A lot of research has been done for reducing SLA violation with number of migrations for different algorithms. MBFD algorithm is considered as one of the algorithm that has introduced VM \nallocation in cloud computing and is considered as one of the best algorithm for providing better results as compare to other algorithms like Skewness and Network aware approach. Therefore, in this research, MBFD algorithm has been analyzed and executed along with neural network as a classification approach for predicting the allocation error. Parameters, namely, Allocation strength and error rate are considered for analyzing the whole process. The whole simulation has been carried out in CLOUDSIM 2.0 environment along with NetBeans.
Author: Kakkar, Devika
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7000982241