Abstract:In the Internet of Things (IoT), edge computing can provide real-time performance of IoT computing and reduce the amount of data transmitted in the network. In order to satisfy the development of the IoT technology, we study the IoT network using software defined network (SDN) architecture in this paper, and use the method provided by SDN to measure the traffic in the network. Fine-grained traffic measurement can more accurately describe traffic in the network, but it also consumes a lot of measurement overhead. In order to reduce the overhead generated in the measurement process and obtain approximate fine-grained measurements, this paper proposes an IoT network traffic measurement scheme based on edge computing. The new measurement architecture uses coarse-grained measurements and interpolation optimization to measure. First, we use the random sampling method to measure coarse-grained network traffic through OpenFlow protocol. Then, the coarse-grained network traffic is interpolated and restored, and the multi-constraint optimization method is used to optimize the interpolation result until the optimal fine-grained flow measurement result that satisfies the condition constraint is found. Finally, the feasibility and effectiveness of the proposed measurement method are verified by experiments.