A Scalable and Offloading-Based Traffic Classification Solution in NFV/SDN Network Architectures

Service Function Chaining (SFC) is an enabling technology to provide end-to-end service differentiation according to specific user requirements. Although emerging technologies such as Software-Defined Networking (SDN) and Network Function Virtualization (NFV) are perfect enablers for SFC, hardware limitation of Ternary-Content Addressable Memories (TCAMs) can be an obstacle when handling a large variability of SFC requests, derived from the increasing number of users, and the heterogeneity of applications and Quality of Service (QoS) requirements. This article introduces and investigates the problem of TCAM size limitation on the classification procedure of SFC requests in SDN-based SFC environments. To overcome this limitation, the classification of incoming SFC requests is proposed to be offloaded to transient nodes when the occupation of the ingress node flow table is close to its maximum. An Integer Linear Programming (ILP) formulation is provided to formalize the Chain Request Classification Offloading (CRCO) problem, that consists in maximizing the number of SFC requests that can be served. Furthermore, a heuristic algorithm is presented to solve the CRCO problem in feasible time. The performance evaluation carried out over two real topologies, shows that the proposed offloading strategy can greatly increase the number of accepted requests without significantly affecting the network QoS.