Traffic-aware efficient consistency update in NFV-enabled software defined networking

Abstract

In network function virtualization(NFV)-enabled software defined networks, the controller needs to frequently update the flow forwarding rules in the data plane to adapt to dynamic changes in network topologies or service requests. However, inconsistent rule updates may lead to blackholes, loops, transient congestion or policy violations (e.g., packets do not traverse designated network functions in a specific order), resulting in service interruption and throughput degradation. Therefore, this paper proposes an effective rule consistent update mechanism to avoid the above four problems simultaneously, while improving network throughput and satisfying user requests. Specifically, we first build three effective models to avoid blackholes, loops, and policy violations. Then, considering that network function nodes may change the sizes of their processed flows, we build a congestion avoidance model based on traffic changes to avoid congestion, which can reduce unnecessary rule update delays and packet loss. Subsequently, we prove that the consistent update problem constructed above is NP-hard, and then design an effective heuristic rule consistent update algorithm to obtain the rule update sequence that can simultaneously avoid blackholes, loops, congestion, and policy violations. Extensive trace-driven simulation results show that compared with the existing update methods, our proposed method can improve the success rate by up to 20.6% and reduce the maximum link utilization by up to 7.5%.