An Off-line Analytical Approach to Identify Suitable Management Policies for Autonomic Cloud Architecture

Delivering cloud services with better quality-of- service demands infrastructures which are autonomic and self- manageable. In particular, there is a clear scope for developing automated methods for enforcing suitable management policies that would run such infrastructures. An example of a management policy is the one that governs the triggering of migration of virtual machines to manage energy consumption. Although there is extensive research on developing novel methods of implementing such policies in an autonomic manner, the identification of suitable policies in terms of cost reduction has received less attention. This requires an analysis of two given sets of policies to identify which one is more suitable. This paper presents a method involving Coloured Petri Nets for an offline modelling and analysis of an autonomic cloud platform which executes sets of policies. We use traces of execution in Petri Nets for calculating minimum cost associated to each set of policies. Petri Net models can generate infinite traces because of the appearance of loops. However, as migration of virtual machines entails cost, many of the infinite traces will not result in the identification of the minimal cost. This paper presents an analytical method using Integer Programming to find the minimum cost of energy consumption for a given policy. We evaluated our approach with the help of an energy management case study.