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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Gang Wang Gui-zhen Chen Shen Zhang |
| Copyright Year | 2009 |
| 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. First, we measures the packet loss rate in different communication distance and the noise power density in underground straight laneway. 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. Then, 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. At last, the simulation based on the QoS routing algorithm by NS2 software verifies the superiority of this method. |
| Starting Page | 125 |
| Ending Page | 129 |
| File Size | 310319 |
| Page Count | 5 |
| File Format | |
| ISBN | 9780769535074 |
| DOI | 10.1109/CSIE.2009.722 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-03-31 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Tree data structures Density measurement Quality of service Wireless sensor networks (WSNs) Convergence Wireless communication Quality of Service (QoS) Wireless sensor networks Power measurement Neural network (NN) Neural networks Clustering algorithms Data communication |
| Content Type | Text |
| Resource Type | Article |
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