Ant system for service deployment in private and public clouds

Large-scale computing platforms that serve thousands or even millions of users through the Internet are on a path to become a pervasive technology available to companies of all sizes. However, existing technologies to enable this kind of scaling are based on a hierarchically managed approach that does not scale equally well. Moreover, existing systems are also not equipped to handle the dynamism that may emerge as a result of severe failures or load surges. In this paper, we conjecture that using self-organizing techniques for system (re)configuration can improve both the scalability properties of such systems as well as their ability to tolerate churn. Specifically, the paper focuses on deployment of virtual machine images onto physical machines that reside in different parts of the network. The objective is to construct balanced and dependable deployment configurations that are resilient. To accomplish this, a method based on a variant of Ant Colony Optimization is used to find efficient deployment mappings for a large number of virtual machine image replicas that are deployed concurrently. The method is completely decentralized; ants communicate indirectly through pheromone tables located in the nodes. An example scenario is presented and simulation results are obtained for the method.