Identification of Communication State for Wireless Sensor Networks

In the process of wireless sensor network communication, the communication state of network is a quite important research point. Network communication strategy needs to be adjusted to ensure the overall performance when the network throughput overloads. Therefore, we need to identify the state of network transmission as the guidance of network communication strategy adjustment firstly. In this paper, we design and implement a real-time online mechanism to identify the communication state of the sensor networks, which can accurately determine whether the network transmission state is normal or overload, to support the adjustment of communication strategy. We obtain the basic performance parameters of the process of transmission by experiments, and analyze the correlation between these parameters and the communication state. Then, we select throughput as the classification criteria of the network communication state, and establish the identification model of communication state based on the support vector machines (SVM), and obtain the parameters of the model in the simulated environment according to the experimental data. Evaluation result shows that the accuracy of the identification model can be achieved up to 91.28%, which can effectively identify the communication state for wireless sensor networks.