Performance modeling and analysis of an autonomic router

Modern networking is moving towards exploitation of autonomic features into networks to reduce management effort and compensate the increasing complexity of network infrastructures, e.g. in large computing facilities such the data centers that support cloud services delivery. Autonomicity provides the possibility of reacting to anomalies in network traffic by recognizing them and applying administrator defined reactions without the need for human intervention, obtaining a quicker response and easier adaptation to network dynamics, and letting administrators focus on general system-wide policies, rather than on each component of the infrastructure. The process of defining proper policies may benefit from adopting model-based design cycles, to get an estimation of their effects. In this paper we propose a model-based analysis approach of a simple autonomic router, using Stochastic Petri Nets, to evaluate the behavior of given policies designed to react to traffic workloads. The approach allows a detailed analysis of the dynamics of the policy and is suitable to be used in the preliminary phases of the design cycle for a Software Defined Networks compliant router control plane.