Joint Optimization of Scaling and Placement of Virtual Network Services

The management of complex network services requires flexible and efficient service provisioning as well as optimized handling of continuous changes in the workload of the services. To adapt to changes in the demand, service components need to be replicated (scaling) and allocated to physical resources (placement) dynamically. In this paper, we propose a fully automated approach to the joint optimization problem of scaling and placement, enabling quick reaction to changes. We formalize the problem, analyze its complexity, and develop two algorithms to solve it. Empirical results show the applicability and effectiveness of the proposed approach.