Research On Reliable Acquisition And Transmission Of Event-driven Hierarchical WSNs

With the development of intelligent sensor technology,the application scenarios of wireless sensor networks(WSNs)are more extensive,followed by the users of the network data reliability requirements are also increasingly high,especially in the event monitoring system.Due to the special properties and working environment of sensing nodes in wireless sensor networks,it is easy to affect the process of data acquisition and transmission,especially in event monitoring networks which have higher requirements for data quality.This paper takes event-driven layered wireless sensor network as the model and combines the characteristics of monitoring events to deeply study the reliable data collection at the sensing end of the event monitoring network and the impact of sudden network congestion on reliable data transmission,and puts forward the corresponding solutions.(1)To solve the problem of reliable data acquisition at the sensing end,a reliable data acquisition method based on the trust model is proposed.The method improves the historical limitation of the trust model through the data offset,and divides"abnormal data" according to the characteristics of the event data flow and historical information.For small scale data anomalies,the credibility of the abnormal data is judged based on the trust model,the data with high reliability is uploaded in time,and the data with low reliability is filtered.In addition,a set of emergency data transmission mechanism is designed for large-scale data anomalies caused by monitoring events.The scheme improves the reliability of data acquisition at the sensing end and lays a foundation for reliable data transmission.(2)For emergency caused data flow surge associated cluster head nodes congestion problem,this paper proposes a congestion control and mitigation scheme based on Kalman filter,this method first based on Kalman filtering theory on the basis of the current cache queue situation of cluster head to predict the next moment the queue status,and combining the cluster head throughput forecasting on network congestion situation.In addition,the degree of network congestion is divided by the congestion threshold,and corresponding control schemes are used for different degrees of congestion to meet the needs of the event monitoring system.This scheme provides a guarantee for reliable data transmission by improving the adaptability and robustness of cluster head nodes.And the comparison of simulation experiments shows that the improved trust model has high reliability in anomaly detection of event data stream,and the average detection accuracy is about 9.14%higher than that of the classical trust model RFSN algorithm,and the accumulation effect of trust is obvious.In addition,the congestion control scheme based on Kalman filter reduces network delay by about 10%compared with the CODA algorithm,and has better performance in reducing network energy consumption and prolonging network life cycle.Figure[24]Table[4]Reference[61]...