Research on Link Quality Estimation Mechanism for Wireless Sensor Networks Based on Support Vector Machine

摘要

In the application of Wireless sensor net-works (WSNs), effective estimation for link quality is a basic issue in guarantying reliable data transmission and upper network protocol performance. A link quality es-timation mechanism is proposed, which is based on Sup-port vector machine (SVM) with multi-class classification. Under the analysis of the wireless link characteristics, two physical parameters of communication, Receive sig-nal strength indicator (RSSI) and Link quality indicator (LQI), are chosen as estimation parameters. The link qual-ity is divided into five levels according to Packet recep-tion rate (PRR). A link quality estimation model based on SVM with decision tree is established. The model is built on kernel functions of radial basis and polynomial re-spectively, in which RSSI, LQI are the input parameters. The experimental results show that the model is reason-able. Compared with the recent published link quality es-timation models, our model can estimate the current link quality accurately with a relative small number of probe packets, so that it costs less energy consumption than the one caused by sending a large number of probe packets. So this model which is high efficiency and energy saving can prolong the network life.