{"title":"无线传感器网络QoS测量中SOM的研究","authors":"G. Wang, S. Zhang","doi":"10.1109/CCPR.2008.95","DOIUrl":null,"url":null,"abstract":"Due to the quality of service issues that wireless communications for data transmission need to ensure, we use the SOM neural network for QoS pattern space convergence, and apply cluster results to the shortest path algorithm in sensor networks. This paper constructs a wireless sensor networks packet loss rate test model of Simulink, and uses it to measure the packet loss rate in different communication distance and the noise power density. From these we obtain the SOM network input samples. After network training, the convergent vector matrix and the corresponding quality of service function are obtained. Finally, we apply the quality of service to the shortest path tree structure, and evaluate the performance of pattern recognition in the shortest path tree structure by NS2 software.","PeriodicalId":292956,"journal":{"name":"2008 Chinese Conference on Pattern Recognition","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Study on SOM in Wireless Sensor Networks QoS Measurement\",\"authors\":\"G. Wang, S. Zhang\",\"doi\":\"10.1109/CCPR.2008.95\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Due to the quality of service issues that wireless communications for data transmission need to ensure, we use the SOM neural network for QoS pattern space convergence, and apply cluster results to the shortest path algorithm in sensor networks. This paper constructs a wireless sensor networks packet loss rate test model of Simulink, and uses it to measure the packet loss rate in different communication distance and the noise power density. From these we obtain the SOM network input samples. After network training, the convergent vector matrix and the corresponding quality of service function are obtained. Finally, we apply the quality of service to the shortest path tree structure, and evaluate the performance of pattern recognition in the shortest path tree structure by NS2 software.\",\"PeriodicalId\":292956,\"journal\":{\"name\":\"2008 Chinese Conference on Pattern Recognition\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-10-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 Chinese Conference on Pattern Recognition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCPR.2008.95\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 Chinese Conference on Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCPR.2008.95","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Study on SOM in Wireless Sensor Networks QoS Measurement
Due to the quality of service issues that wireless communications for data transmission need to ensure, we use the SOM neural network for QoS pattern space convergence, and apply cluster results to the shortest path algorithm in sensor networks. This paper constructs a wireless sensor networks packet loss rate test model of Simulink, and uses it to measure the packet loss rate in different communication distance and the noise power density. From these we obtain the SOM network input samples. After network training, the convergent vector matrix and the corresponding quality of service function are obtained. Finally, we apply the quality of service to the shortest path tree structure, and evaluate the performance of pattern recognition in the shortest path tree structure by NS2 software.