Joint virtual machine and bandwidth allocation in software defined network (SDN) and cloud computing environments

Abstract

Cloud computing provides users with great flexibility when provisioning resources, with cloud providers offering a choice of reservation and on-demand purchasing options. Reservation plans offer cheaper prices, but must be chosen in advance, and therefore must be appropriate to users' requirements. If demand is uncertain, the reservation plan may not be sufficient and on-demand resources have to be provisioned. Previous work focused on optimally placing virtual machines with cloud providers to minimize total cost. However, many applications require large amounts of network bandwidth. Therefore, considering only virtual machines offers an incomplete view of the system. Exploiting recent developments in software defined networking (SDN), we propose a unified approach that integrates virtual machine and network bandwidth provisioning. We solve a stochastic integer programming problem to obtain an optimal provisioning of both virtual machines and network bandwidth, when demand is uncertain. Numerical results clearly show that our proposed solution minimizes users' costs and provides superior performance to alternative methods. We believe that this integrated approach is the way forward for cloud computing to support network intensive applications.