A topology-aware adaptive deployment framework for elastic applications

In Distributed Cloud Computing, applications are deployed over thousands of geographically distributed cloud sites. This new deployment approach promises not only improved application´s quality of service but enables deploying network-critical applications otherwise not possible. A previously settled, static allocation of enough resources at each site is expensive. Adapting resource allocations during application lifetime could dramatically reduce expenses. They are triggered by complex algorithms as a reaction of changes in measured performance data. However, such adaptation algorithms and their performance data depends on specific application´s requirements, constrains, and on optimization goals. Some interactive applications need a low packet round trip time. Other streaming applications need a high data rate to the user. Besides these individual characteristics of an adaptation, similarities exists in the management of such a geographical distribution: Applications and their components are deployed within Virtual Machines. The components have to find and communicate with each other. Motivated by this, we present a framework taking care of necessary common functionality while been highly customizable to support a wide range of adaptation. Additionally, integrated adaptations can utilize combined application- and infrastructure- level data and are also able to reconfigure the application and the infrastructure. Finally, a steering-system supports state-ful and multi-tier applications to be deployed in an elastic and dynamic way.