Deploying Time-based Sampling Techniques in Software-Defined Networking

Abstract

Network data volumes have seen a substantial increase in recent years, in part due to the massive use of mobile devices, the dissemination of streaming services and the rise of concepts such as IoT. This growing trend highlights the need to improve network monitoring systems to cope with challenges related with performance, flexibility and security. Software-Defined Networking (SDN) and traffic sampling techniques can be combined to provide a toolset that can be used for enhancing network management activities and performance evaluation. In this context, this paper presents a proposal for supporting time-based sampling techniques in SDN, providing network statistics at the controller level and allowing the self-configuration of traffic sampling in network devices. The proposed solution, designed to improve the efficiency and flexibility of network measurement systems, takes into account the underlying need to establish a balance between the reliability of the collected data and the computational effort involved in the sampling process. The proof-of-concept results emphasize the potential of applying and configuring different time-based sampling techniques through a SDN framework and a small set of standard OpenFlow messages. Comparative results on the accuracy and overhead of each technique when sampling real traffic traces are also provided.