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.INDEX TERMS Hierarchical heavy hitter, software-defined networking, dynamic resource allocation.

Towards threshold‐agnostic heavy‐hitter classification

“…Recently developed methods suggest implementing auxiliary devices that can offload the burden caused by metering tens of thousands of active flows per second. 48,49 In switch-based approaches, 10,23,[50][51][52][53][54][55][56][57][58] the task of HHs identification is moved from the controller to the switches. 54,59 Research works aimed at the viability evaluation of switch-based HH classification has, however, shown that practical deployment of such techniques is minimal, mainly due to the high costs of hardware modifications the implementations require.…”

“…In switch‐based approaches, 10,23,50–58 the task of HHs identification is moved from the controller to the switches 54,59 . Research works aimed at the viability evaluation of switch‐based HH classification has, however, shown that practical deployment of such techniques is minimal, mainly due to the high costs of hardware modifications the implementations require 60–62 .…”