A Dynamic Virtual Machine Allocation Technique Using Network Resource Contention for a High-performance Virtualized Computing Cloud

Virtualized Computing Cloud (VCC) is a well-known resource-provisioning and computing environment due to advantages such as maximized resource utilization, isolated performance, and customizable runtimes. Therefore, recently, VCC has been increasingly adopted in a broad spectrum of service domains, including internet-based application services and computational science. However, efficient resource (i.e., virtual machine; VM) allocation techniques are required to deliver higher-quality Internet and/or computing services. In this paper, we propose a novel dynamic, self-adaptive VMs allocation technique considering network resource contention in a Xen virtualization environment. In addition, we provide generic virtualized resources and job management framework to realize our proposed VM allocation technique. Using the virtualized resources and job management framework, we also practically analyze the impact of various system parameters and job characteristics on the performance of our technique. The results show that our approach outperforms others, reducing the average job response (by up to 37%) and execution (by up to 22.3%) times.