Optimal provisioning for elastic service oriented virtual network request in cloud computing

In the cloud computing paradigm users access applications/services hosted and run on virtual machines in interconnected datacenters. Applications from the same user may need to interact and change data or information, thus, we may abstract the applications/services request from same user as a virtual network (VN). To improve performance and resource efficiency, it is critical that the VN request be optimally provisioned given the current resource state of the datacenters. However, all of the existing research about optimal VN provisioning conducted for deterministic services. In this work, we formulate the problem of optimal provisioning for elastic service oriented VN request as a mixed integer programming (MIP) model with the objective of maximizing the total revenue of infrastructure provider (InP), and propose a genetic algorithm based heuristic (GAH) algorithm for addressing the optimal provisioning for virtual network request with un-splittable flow (OPVNUF) and optimal provisioning for virtual network request with splittable flow (OPVNSF) problems of elastic services. We demonstrate the effectiveness of our approach for improving the total revenue, by conducting extensive simulations on real substrate network.