STOCHASTIC MARKOV MODEL APPROACH FOR EFFICIENT VIRTUAL MACHINES SCHEDULING ON PRIVATE CLOUD

Cloud computing is deployed a large set of virtualized computing resources in different infrastructures and various development platforms. One of the significant issues in cloud computing system is the scheduling and allocation of virtual resources and virtual machines (VMs). To address this issue, this paper proposed an efficient approach for virtual machines scheduling in cloud infrastructure resource management and allocation also called EVMSA (Efficient Virtual Machines Scheduling Algorithm) that provides the effective and efficient resource allocation. To analyze the performance of this scheduling and allocation on cloud infrastructure, an analytical performance model approach using Stochastic Markov model is proposed to measure the scalability and tractability for infrastructure resource of private cloud. This model intends to analyze an academic-oriented private cloud system which is implemented using Eucalyptus open source system. According to performance evaluation, the effective mean response time of the system to improve the performance of IaaS services in the system