SONATA: Service Programming and Orchestration for Virtualized Software Networks

In conventional large-scale networks, creation and management of network services are costly and complex tasks that often consume a lot of resources, including time and manpower. Network softwarization and network function virtualization have been introduced to tackle these problems. They replace the hardware-based network service components and network control mechanisms with software components running on general-purpose hardware, aiming at decreasing costs and complexity of implementing new services, maintaining the implemented services, and managing available resources in service provisioning platforms and underlying infrastructures. To experience the full potential of these approaches, innovative development support tools and service provisioning environments are needed. To answer these needs, we introduce the SONATA architecture, a service programming, orchestration, and management framework. We present a development toolchain for virtualized network services, fully integrated with a service platform and orchestration system. We motivate the modular and flexible architecture of our system and discuss its main components and features, such as function- and service-specific managers that allow fine- grained service management, slicing support to facilitate multi-tenancy, recursiveness for improved scalability, and full-featured DevOps support

Response-Time-Optimized Distributed Cloud Resource Allocation

A current trend in networking and cloud computing is to provide compute resources over widely dispersed places exemplified by initiatives like Network Function Virtualisation. This paves the way for a widespread service deployment and can improve service quality; a nearby server can reduce the user-perceived response times. But always using the nearest server is a bad decision if that server is already highly utilized. This paper investigates the optimal assignment of users to widespread resources -- a convex capacitated facility location problem with integrated queuing systems. We determine the response times depending on the number of used resources. This enables service providers to balance between resource costs and the corresponding service quality. We also present a linear problem reformulation showing small optimality gaps and faster solving times; this speed-up enables a swift reaction to demand changes. Finally, we compare solutions by either considering or ignoring queuing systems and discuss the response time reduction by using the more complex model. Our investigations are backed by large-scale numerical evaluations