A multi-objective software defined network traffic measurement. (January 2017)

• Record Type: Journal Article
• Authors: Tahaei, Hamid; Salleh, Rosli; Khan, Suleman; Izard, Ryan; Choo, Kim-Kwang Raymond; Anuar, Nor Badrul
• Is Part Of: Measurement. Volume 95(2017)
• Page Start: 317
• Page End: 327
• Publication Date: 2017-01
• Subjects: Software defined measurement -- Software defined networking -- Network monitoring; Weights and measures -- Periodicals; Measurement -- Periodicals; Measurement; Weights and measures; Periodicals; 530.8
• DOI: 10.1016/j.measurement.2016.10.026
• Languages: English
• ISSNs: 0263-2241

Abstract

Graphical abstract: Highlights: A multi-objective software defined network traffic measurement. Accurate real-time traffic matrix for the traffic measurement system. Elastic polling scheme for software defined networking. Fine-grained monitoring task. Abstract: Software Defined Networking (SDN) with defining characteristics, such as "separation of data and control plane" and "centralizing network control with decision making", has significantly simplified network management. However, active monitoring techniques used to dynamically measure network traffic introduce additional overheads in the network, while a passive approach lacks accuracy in terms of traffic measurement. As a result, various efforts have been devoted to designing per-flow based network measurement system to address both accuracy and overhead challenges. Existing measurement techniques lack a multi-objective network measurement mechanism to overcome various overheads, like communication cost, controller computation, and accuracy in a real-time environment. Therefore, this paper presents a novel and practical solution to enable accurate real-time traffic matrix for the traffic measurement system in SDN. The solution is proposed to measure fine-grained monitoring task with less controller communication and computational cost with high accuracy. The solution is based on two measurement designs, namely: fixed and elastic schemas. Our experiments demonstrate that both fixed and elastic schemas achieve significant overhead reduction without compromising on accuracy.