| River ice environment monitoring forms the basis for disaster monitoring and provides important evidence for disaster forecast,flood control,drought relief,and water quality monitoring.In the river ice environment monitoring work,it is very important to use the data acquisition and wireless sensor network remote monitoring to realize the timely prediction and alarm of disasters.In the actual composition of the ice detection system,the use of various new ice sensor,the continuous expansion of the monitoring range,and the existence of a large number of singular(interference)ice signals caused by the harsh working environment.These phenomena have led to the data acquisition,the real-time processing of the on-site ice signal and the increase of the long-distance transmission of the ice signal,which has increased the burden of the ice monitoring network and affected the quality and real-time of the data.Therefore,it is urgent to study the new ice detection equipment and real-time processing algorithm of ice data that can be applied to the actual project site,and introduce new data communication methods and networking structures to meet the needs of ice detection.In the past few decades,mobile data traffic has grown tremendously,driving a huge shift in wireless networks.In the 5G access network technology,how to provide data-intensive and delay-sensitive applications for a large number of users has been a research hotspot.The F-RAN is considered to be an effective solution.Extending the caching and computing network functions from the remote cloud server to the edge of the user device reduces the burden on the backhaul link and significantly improves network performance.In order to overcome the shortcomings of existing ice detection network,this paper introduces 5G wireless F-RAN network and wireless sensor network networking technology into ice detection network,and proposes a data transmission method based on 5G wireless F-RAN network hierarchical content distribution.Combining with the specific environment of ice condition detection,the principle of fog wireless network is used to solve the problem of low data transmission rate and limited analysis among deployed detection devices.At the same time,in order to solve scheduling conflicts in the process of front-end wireless sensor network networking,a clustering scheme based on dynamic priority scheduling is proposed to build sensor networks.Aiming at the problem of data fusion in front-end data transmission,an improved K-means adaptive weighting algorithm is proposed to realize data fusion of various types of sensors.In the back-end,the elastic BP network is used to train the collected data and establish the data model base,so that the data can be presented in real time at the back-end,and the overall situation of the river ice-water environment can be determined.The main research contents are summarized as follows.1.Based on the summary research of several types of new ice and snow detection sensors and detection principles researched by the research group for many years,combined with the characteristics of existing sensors,the NB-Io T wireless communication technology is integrated to the detection sensor system,and the sensor is improved from the communication structure.It can be directly applied to the next-generation intelligent terminal equipment of 5G network,and has the wireless sensor network networking capability,which lays a foundation for the application of the Internet of Things technology to the river ice environment detection system.2.In this paper,based on the research of front-end wireless sensor network networking technology,a clustering scheme based on dynamic priority scheduling is proposed to build a sensor network.An improved K-means data algorithm is proposed to achieve the fusion of multiple types of data.The clustering scheme is used to build the sensor network,and the multi-data fusion algorithm is used to realize the fusion of data collected by various types of sensors at the sensor cluster node to realize the transmission of effective data.At the same time,the flexible BP network is used for training and the data model library is built to make the data.It is possible to determine the overall condition of the river ice environment in real time at the back end.The algorithm solves the problem that the existing sensor network increases in various sensor nodes,the network load increases when the deployment is dense,and the network lifetime decreases.It is suitable for experimental research in low temperature and complex environments.Through simulation verification and comparison test,the algorithm can realize the efficient and accurate transmission of data collected by various types of sensors by using existing sensor networks,and achieve the goal of real-time detection of river ice environment.3.Based on the 5G fog wireless network transmission architecture,combined with the specific environment of ice detection,a new F-RAN layered content distribution strategy is studied.Under the proposed layered content distribution policy,a C-UE with a random file request and its associated BS and F-UE jointly and hierarchically provide services within a range of distance.According to the transmission theory of the new F-RAN layered content distribution strategy,the basic principles of the content distribution strategy are introduced in detail.The transmission probability of the BS in the F-RAN is derived.Then,under the assumption of the scattered probability buffer placement,the average transmission probability of the F-UE is further derived.Under the layered content distribution strategy,this paper first evaluates the conditional cache hit probability.Then,the analytical expression of the coverage probability is derived.After that,the SCDP of the F-RAN was analyzed.The simulation results verify the analysis results,and the proposed layered content distribution strategy can significantly improve the quality of F-RAN experience,and meet the needs of efficient simultaneous interpreting and transmitting of large video data files in multiple terminal devices. |
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