Adaptive Genetic Algorithm for Efficient Resource Management in Cloud Computing
S. R. Suraj, R Natchadalingam · 2014
Cloud is one of the emerging technologies in computer industry. Several companies migrate to this technology due to reduction in maintenance cost. Several organizations provide cloud service such as SaaS, IaaS, PaaS. Different organization provides same service with different service charges and waiting time. So customers can select services from these cloud providers according to their criteria like cost and waiting time. In existing and current system is based only on future load prediction mechanism. Based on this factor VM resource allocation is done. During this VM migration, there is no suitable criteria for unique identification and location of VM, that means which VM is migrated and where to be migrated. In this paper a Cloud Booster Algorithm is using. In this system VM allocation is based on node weight (a value indicates capacity of each node). Based on these weights a VM resource allocation mechanism has proposed, which is considering both Node weight and future prediction. To produce a better approach for solving the problem of VM resource migration in a cloud computing environment, this project demonstrates Adaptive Genetic Algorithm based VM resource migration strategy that focuses on system load balancing.