Improving dynamic service function chaining classification in NFV/SDN networks through the offloading concept

Abstract

Service Function Chaining (SFC) paradigm improves network capabilities thanks to the support of application-driven-networking, which is realized through the invocation of an ordered set of Service Functions (SFs). The programmability and flexibility provided by emerging technologies such as Software-Defined Networking (SDN) and Network Function Virtualization (NFV) are perfect features for efficiently managing the lifecycle of SFCs. However, the limitation of Ternary Content Address Memories (TCAMs) of the SDN nodes in SDN-based SFC scenarios can lead to network performance degradation when the SFC classifier is not able to install new classification rules. To tackle the Dynamic Chain Request Classification Offloading (D-CRCO) problem presented in this paper, a hybrid eviction and split-and-distribute approach is proposed, where i) the dynamic behavior of SFC requests is exploited by removing the corresponding idle rules from the flow tables if necessary; and ii) SFC classification is not forced to be carried out by the ingress node, but by any transit node in the domain. An Integer Linear Programming (ILP) formulation and an heuristic are provided to solve D-CRCO, with the goal of maximizing the number of SFC requests that can be served, respecting TCAM size, link capacity, and SF availability constraints. Simulation and emulation results over two real topologies show that the proposed solution is able to significantly increase the number of served SFC requests with a negligible impact on the network performance.