{"title":"Clock synchronization using maximal margin estimation","authors":"Dani E. Pinkovich, N. Shimkin","doi":"10.1109/MED.2011.5983128","DOIUrl":null,"url":null,"abstract":"Clock synchronization in a network is a crucial problem due to the wide use of networks with simple nodes, such as the internet, wireless sensor networks and Ad Hoc networks. We present novel algorithms for synchronization of pairs of clocks based on Maximum Margin Estimation of the offset and skew between pairs of clocks. Our algorithms are inspired by the well known Support Vector Machines algorithm from the Machine Learning literature and have sound geometrical intuition for our model. In addition, we provide a modification to our algorithms (also relevant for the existing LP algorithm) to enhance their robustness to measurement outliers. Finally, we analytically derive the Mean Square Error for the estimation of offset, in the special case when the skew is given. Simulation experiments demonstrate that our algorithms have significantly better performance than state of the art synchronization algorithms.","PeriodicalId":146203,"journal":{"name":"2011 19th Mediterranean Conference on Control & Automation (MED)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 19th Mediterranean Conference on Control & Automation (MED)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MED.2011.5983128","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Clock synchronization in a network is a crucial problem due to the wide use of networks with simple nodes, such as the internet, wireless sensor networks and Ad Hoc networks. We present novel algorithms for synchronization of pairs of clocks based on Maximum Margin Estimation of the offset and skew between pairs of clocks. Our algorithms are inspired by the well known Support Vector Machines algorithm from the Machine Learning literature and have sound geometrical intuition for our model. In addition, we provide a modification to our algorithms (also relevant for the existing LP algorithm) to enhance their robustness to measurement outliers. Finally, we analytically derive the Mean Square Error for the estimation of offset, in the special case when the skew is given. Simulation experiments demonstrate that our algorithms have significantly better performance than state of the art synchronization algorithms.