Performance analysis of cloud with queue-dependent virtual machines

Cloud computing provides a new way for industries to meet the emerging business need for agility. Many public clouds are available for developers to build web applications on cloud. The process of entering into the cloud is generally in the form of a queue, so that each user need to wait until the current user is being served. In the system, each Cloud Computing User (CCU) requests Cloud Computing Service Provider (CCSP) for use of resources. If CCU finds the server busy, then the user has to wait till the current user completes the job. This may result in increase of queue length as well as waiting time, which may lead to request drop. To handle this problem, CCSP needs to find ways to reduce waiting time. We propose a finite multiserver queueing model with queue dependent heterogeneous servers where the web applications are modeled as queues and the virtual machines are modeled as service providers. CCSP's can use multiple servers and the number of busy servers changes depending on the queue length for reducing queue length and waiting time. This helps us to dynamically create and remove virtual machines in order to scaling up and down. We develop a recursive method to obtain the system steady-state probabilities. Various performance measures of the proposed scheme have been described and evaluated. Computational experiences in the form of graphs are presented.