Research Article
A Network Traffic Measurement Approach for Edge Computing Networks
@INPROCEEDINGS{10.1007/978-3-030-97124-3_3, author={Xi Song and Wansheng Cai and Chuan Liu and Dingde Jiang and Liuwei Huo}, title={A Network Traffic Measurement Approach for Edge Computing Networks}, proceedings={Simulation Tools and Techniques. 13th EAI International Conference, SIMUtools 2021, Virtual Event, November 5-6, 2021, Proceedings}, proceedings_a={SIMUTOOLS}, year={2022}, month={3}, keywords={Edge computing Internet of things Software defined networking}, doi={10.1007/978-3-030-97124-3_3} }- Xi Song
Wansheng Cai
Chuan Liu
Dingde Jiang
Liuwei Huo
Year: 2022
A Network Traffic Measurement Approach for Edge Computing Networks
SIMUTOOLS
Springer
DOI: 10.1007/978-3-030-97124-3_3
Abstract
Edge computing is one of the key technologies in 5G networks, it can collect and process data on the access network and decrease the transmission load of the network. The data exchange in the Edge computing network Software Defined Networking (SDN) decouples the control plane and forwarding plane in traditional switches and plans to route in the global view, making network management more flexible and efficient. The accurate and comprehensive network traffic measurement is the key to traffic management of edge computing networks. Then, we propose a novel edge computing network traffic measurement approach to SDN. The proposed measurement methods use the in SDN by collecting statistics in OpenFlow-based switch and utilize the LSTM model and GNN method to infer the fine-grained measurement. Then, we construct an objective function to optimize the estimation results. Finally, we conduct a series of simulations to evaluate the performance of the proposed scheme. Simulation results show that our approach is feasible and has low measurement cost.
