A software‐defined networks‐based measurement method of network traffic for 6G technologies. Issue 4 (13th November 2020)

• Record Type: Journal Article
• Authors: Huo, Liuwei; Jiang, Dingde; Lv, Zhihan
• Other Names: Cheng Xiaochun guestEditor.; Liu Zheli guestEditor.; Ning Yongsheng guestEditor.
• Is Part Of: Transactions on emerging telecommunications technologies. Volume 33:Issue 4(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-11-13
• Subjects: Telecommunication -- Periodicals; 384.05
• DOI: 10.1002/ett.4172
• Languages: English
• ISSNs: 2161-5748

Abstract

Abstract: In software‐defined networks (SDN) for 6G technologies, the controller should accurately and efficiently measure the flow traffic in switches for traffic engineering. Fine‐grained flow measurement can more accurately describe the traffic in the network, but it also consumes much more resources. To reduce the overhead incurred in the measurement process and obtain the approximate fine‐grained measurements, we propose a novel lightweight measurement scheme that runs in the controller. The novel lightweight measurement architecture consists of two parts: coarse‐grained measurement and interpolation‐optimization. In the first part, based on the SDN architecture, we use the pull‐based random sampling method to quickly obtain the coarse‐grained measurement of flow traffic through OpenFlow protocol. In the second part, we insert some discrete values into the coarse‐grained measurement with the interpolation theory, then we optimize interpolation results until finding the optimal fine‐grained flow traffic measurement by utilizing the multiconstraint method. We verified the feasibility of the proposed measurement method, and simulation results show that the measurement error of the proposed method is under 25%, but the flow measurement overhead of this method occupies only 3.3% compared with that of the fine‐grained method. Abstract : Accurate and effective network traffic measurement is very important for 6G network management. To accurately measure network traffic while consuming low measurement overhead, we propose a new measurement framework based on SDN for 6G network. First, we utilize the random sampling method to measure the coarse‐grained network. Then, we propose to use interpolation methods to recover fine‐grained network traffic measurements. Finally, we design an objective function and use it to optimize the fine‐grained network traffic measurements to reduce measurement errors.