| dc.description.abstract | Generally, the growth of computing systems has been concentrate on performance improvement or fast processing of applications from the view point of customer, scientific and business perspective. However, this type of computing increases energy consumption. It is continue to consume large amount of energy in the form of electrical power. In cloud computing data center hosting of cloud applications consume huge amount of energy. Optimization of the energy requirements of data center is a very challenging task. This dissertation report describes the energy efficiency of minimization of migration policy in IaaS environment. In this policy VM migration, energy consumption, SLA violations are calculated. VM migration directly influences resource utilization and Quality of Service (QoS) parameters provided by the system. The effect of disturbance cause server overloads, resource shortage, performance degradation etc. So, one of the challenging task is, the placement of VMs, like where, when, which VM could be migrated for saving energy and less SLA violations, with minimum number of migration. In this research work a new approach has been proposed to select VMs to migrate from the over utilized host. Approach migrates those VMs that belongs to the higher category so that that the resources allocated to these VMs have less cost penalties for SLA violations. Proposed approach results are compared to the simulated Minimization of Migration Policy (Beloglazov et al., 2012) and compared its energy requirements, virtual machine migration and SLA violation with Minimum Migration Time and Random Selection policies. | en_US |
