Determining fuzzy link quality membership functions in wireless sensor networks

Abstract

Wireless Sensor Network routing protocols rely on the estimation of the quality of the links between nodes to determine a suitable path from the data source nodes to a data-collecting node. Several link estimators have been proposed, but most of these use only one link property. Fuzzy logic based link quality estimators have been recently proposed which consider a number of link quality metrics. The fuzzification of crisp values to fuzzy values is done through membership functions. The shape of the fuzzy link quality estimator membership functions is primarily performed leveraging qualitative knowledge and an improper assignment of fuzzy membership functions can lead to poor route selection and hence to unacceptable packet losses. This thesis evaluated the Channel Quality membership function of, an existing fuzzy link quality estimator and it was seen that this membership function didn’t perform as well as expected. This thesis presents an experimental approach to determine a suitable Channel Quality fuzzy membership function based on varying the shape of the fuzzy set for a multipath wireless sensor network scenario and choosing an optimum shape that maximizes the Packet Delivery Ratio of the network. The computed fuzzy set membership functions were evaluated against an existing fuzzy link quality estimator under more complex scenarios and it is shown the performance of the experimental refined membership function was better in terms of packet reception ratio and end to end delay.The fuzzy link quality estimator was applied in WiseRoute (a simple converge cast based routing protocol) and shown that this SNR based fuzzy link estimator performed better than the original implemented RSSI based link quality used in WiseRoute.