Towards an Efficient, Scalable, Dynamic and Flexible NFV-based Data Plane

Towards an Efficient, Scalable, Dynamic and Flexible NFV-based Data Plane The increasing demand for complex network functions and middleboxes, and new techniques – SDN and NFV have driven the network transformation from expensive and custom built hardware appliances to predominately software-based NFs (network functions). The heterogeneous software-based NFs and service chains (packets are steered to a sequence of network functions) bring in new challenges and interesting problems such as high speed and flexible networking systems and fine-grained resource management for flow isolation. In this thesis we investigate challenges related to the network data plane, with a particular emphasis on how to provide high performance packet processing, flexible and dynamic flow steering and flow-level resource management and scheduling. We first discuss the limitations of the current divide between an intelligent control plane and an overly simple, stateless data plane. To use fine-grained flow information to determine how packets are processed, we demonstrate OpenNetVM, which provides high-speed packet processing in a flexible data plane. Then we need a way to manage the “smart” data plane with SDN controller. To do so, we present a hierarchical control framework, SDNFV, which can make routing decisions by a SDN controller, a host-level manager and individual NFs based on different granularity information at different stages. The platform provides a flexible and dynamic data plane, which can get the right balance of efficiency, flexibility and ease of control. We then investigate how to provide efficient resource usage and flow-level performance management in the data plane. We propose to leverage the benefits of both polling and interrupt packet processing, that can allow running NFs at a large scale. We track flow state in a light-weight manner and map per flow or per class flows to the required NFs. In Flurries, different types of flows can run and be scheduled on the

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