Abstract
This paper proposes a methodology for prediction traffic flow at the Data Plane (DP) base on SDN and reduce data error based on Kalman filter. This methodology, will help the overall network for forecasting the next step in the packet flow, and therefore lowering the risk of over fitting that may occur. According to the simulation findings, the SDN controller may enhance network Quality of Service (QoS) by reducing packet loss and increasing buffer usage ratios. However, the proposed system used four sensor nodes (such as temperature, humidity) for transmitted data by the NRF24 to the sink node to collected data and upload by ESP32 to the Local cloud by using Wi-Fi network. In this work, one Internet Protocol (IP) to four sensor nodes lowers the data rate to 60%, and the energy consumption by the sensing nodes is lowered by 20% for that using one IP instead using five IP reduce the size of the transmitted packet.
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