E-State: Distributed state management in elastic network function deployments
Manuel Peuster, Holger Karl · 2016
Elastic deployments of virtualized network functions (VNFs) can automatically scale the amount of used resources in relation to their workload. This is often done by starting new VNF instances or stopping old ones. A problem of these scale operations is that most network functions are stateful and their internal state is not automatically migrated when traffic is redistributed. As a result, mechanisms are needed to exchange or migrate internal network function state between VNF instances. This paper presents a state management framework that creates logically distributed state memory on top of elastically deployed VNFs used to share state information between these VNFs. We introduce a novel programming model that provides both a local and a global view of the state to each VNF instance. Further, we compare the performance of our prototype to a centralized and a distributed in-memory database solution.