A Distributed Hierarchical Heavy Hitter Detection Method in Software-Defined Networking

Abstract

Software-defined networking (SDN) enables fast innovation in networks. The management and measurement features that we require can be easily implemented in SDN. However, when simplicity is introduced, SDN also faces some problems, of which the most challenging one is the scalability problem. As the foundation of the networking management, scalability of the traffic measurement is also important. Recently, many works have focused on TCAM-based measurement, which is considered to be scalable and efficient enough. In this paper, we propose a distributed hierarchical heavy hitter (HHH) detection method, which is also a TCAM-based method. Unlike previous works, this method focuses on optimizing the detection speed by dynamically controlling the resource allocated to each measurement task. We propose an efficient solution to solve the optimization problem. The simulation with network-wide tasks and diverse traffic has shown that this method can improve the detection speed when compared with other resource allocation methods, and it can work better under strict resource limitation.