Clustered virtual machines for higher availability of resources with improved scalability in cloud computing

Cloud computing a big pool of resources dynamically reconfigures its resources as per user requirement in real time. Cloud environment mostly works with virtualized environment, which is a key consideration for providing virtual machines as a service to the users. It is difficult to manage virtual machine, and to deploy on any data centers. In cloud environment users expects better services from the vendors, in order to improve resource utilization. The factors in cloud environment as if scalability and availability are consider for better outcomes for users. This not only saves time, but also improves cost utilization. This paper proposes architecture, based on clustering virtual machines in datacenters for higher availability of resources with improved scalability. Clustering helps virtual machines to reconfigure and easy scheduling. The resource sharing in cloud will optimize and users get maximized result. Further, the paper directs a mathematical model for explaining the concepts of the proposed system. The existing system is being modulated using simulation tools and further elaborated in the paper.

I. Introduction

Cloud computing provides almost everything as service to users by its pay per use model. Cloud is a service-oriented technology, which delivers resources on user demand [1]. These resources can be any computational resource that works quite similarly to general computing resources, although resources accessed over internet delays or lags in services due to latency [2]. Another issue is about scaling this cloud environment up to its maximum availability, which maximizes the resource utilization to its extremity. The discovery and scheduling of resources depends on factors like scalability, availability, load balancing, elasticity etc [3]. These factors needs to be considered for making much more reliable system for better cloud model in terms of users direction. The paper explains the need of clustering the Virtual Machine (VM) for better placement and migration in datacenter, for better scheduling the virtual machines architecture for user's utilization of resources.