RW-MC:self-adaptive random walk based matrix completion algorithm
Concerning the continually perceiving performance of virtual access points (VAP) was urgent in software-defined wireless network (SDWN),with the features of VAPs’ measurement data (VMD),a self-adaptive matrix completion algorithm based on random walk was proposed,named RW-MC.Firstly,the discrete rat...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Department of Journal on Communications
2017-09-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2017186/ |
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| Summary: | Concerning the continually perceiving performance of virtual access points (VAP) was urgent in software-defined wireless network (SDWN),with the features of VAPs’ measurement data (VMD),a self-adaptive matrix completion algorithm based on random walk was proposed,named RW-MC.Firstly,the discrete ratio and covering ratio of VMD account for a sample determination model was used to claim initial samples.Secondly,random walk model was implemented for generating sampling data points in the next iteration.Finally,a self-adaptive sampling redress model concerning the differences between the current error rates and normalize error rates of neighboring completion matrices.The experiments show that the approach can collect the real-time sensory data,meanwhile,maintain a relatively low error rate for a small sampling rate. |
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| ISSN: | 1000-436X |