Optimization Algorithm of Time Synchronization Network Monitoring Based on Variational Autoencoder

Bo Lv, Feng Pan, Xinyu Miao, Changjun Hu
{"title":"Optimization Algorithm of Time Synchronization Network Monitoring Based on Variational Autoencoder","authors":"Bo Lv, Feng Pan, Xinyu Miao, Changjun Hu","doi":"10.1109/ICCIA49625.2020.00033","DOIUrl":null,"url":null,"abstract":"In this paper an optimization algorithm for time synchronization in telecommunication network is proposed based on VAE(Variational Auto Encoder)framework. Firstly features are represented in latent space under proposed framework while performance of synchronization network is measured and evaluated. Secondly optimization algorithm is further designed with which feature of abnormal samples and benchmark are adaptively merged for smooth adjustment with low risk in practical network operation. Meanwhile considering the characteristics as domain knowledge of synchronization network, a novel metric is adopted to reduce the fluctuation of adjustment. The simulation results verified that performance of synchronization network is significantly improved by optimization templates reconstructed through decoding part of VAE model. It is implied that prior knowledge of synchronization in latent space is introduced with certain interpret-ability for assessment of monitoring performance while optimization adjustment can be properly operated through novel metric proposed in this algorithm.","PeriodicalId":237536,"journal":{"name":"2020 5th International Conference on Computational Intelligence and Applications (ICCIA)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 5th International Conference on Computational Intelligence and Applications (ICCIA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCIA49625.2020.00033","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

In this paper an optimization algorithm for time synchronization in telecommunication network is proposed based on VAE(Variational Auto Encoder)framework. Firstly features are represented in latent space under proposed framework while performance of synchronization network is measured and evaluated. Secondly optimization algorithm is further designed with which feature of abnormal samples and benchmark are adaptively merged for smooth adjustment with low risk in practical network operation. Meanwhile considering the characteristics as domain knowledge of synchronization network, a novel metric is adopted to reduce the fluctuation of adjustment. The simulation results verified that performance of synchronization network is significantly improved by optimization templates reconstructed through decoding part of VAE model. It is implied that prior knowledge of synchronization in latent space is introduced with certain interpret-ability for assessment of monitoring performance while optimization adjustment can be properly operated through novel metric proposed in this algorithm.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于变分自编码器的时间同步网络监控优化算法
提出了一种基于变分自编码器(VAE)框架的电信网络时间同步优化算法。首先在该框架下将特征用隐空间表示,同时对同步网络的性能进行了测量和评价。其次,进一步设计优化算法,将异常样本特征与基准自适应融合,在实际网络运行中实现平滑调整,降低风险;同时,考虑到同步网络的领域知识特征,采用一种新的度量来减小平差的波动。仿真结果表明,通过解码部分VAE模型重构优化模板,同步网络的性能得到了显著提高。结果表明,该算法引入了潜在空间同步的先验知识,具有一定的可解释性,可用于监测性能的评估,并通过提出的新度量可以正确地进行优化调整。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Does ensemble really work when facing the twitter semantic classification? A Short-Term Hybrid Forecasting Approach for Regional Electricity Consumption Based on Grey Theory and Random Forest A negative selection algorithm based on adaptive immunoregulation ICCIA 2020 Breaker Page Video Prediction and Anomaly Detection Algorithm Based On Dual Discriminator
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1