Yankun Chen, Fei Ji, Q. Guan, Fangjiong Chen, Hua Yu
{"title":"一种新的基于RTT预测的水声网络MAC","authors":"Yankun Chen, Fei Ji, Q. Guan, Fangjiong Chen, Hua Yu","doi":"10.1145/2999504.3001072","DOIUrl":null,"url":null,"abstract":"Most existing medium access control (MAC) protocols in underwater acoustic networks (UANs) ignore the delay variance that affects the estimation accuracy of round trip time (RTT). We predict the RTTs using Bayesian dynamic linear model. Using the predicted RTTs, we dynamically adjust the length of time slots in MAC. Experimental results show that the predicted values can adapt quickly to the delay variance in the acoustic channel.","PeriodicalId":378624,"journal":{"name":"Proceedings of the 11th International Conference on Underwater Networks & Systems","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A new MAC based on RTT prediction for underwater acoustic networks\",\"authors\":\"Yankun Chen, Fei Ji, Q. Guan, Fangjiong Chen, Hua Yu\",\"doi\":\"10.1145/2999504.3001072\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Most existing medium access control (MAC) protocols in underwater acoustic networks (UANs) ignore the delay variance that affects the estimation accuracy of round trip time (RTT). We predict the RTTs using Bayesian dynamic linear model. Using the predicted RTTs, we dynamically adjust the length of time slots in MAC. Experimental results show that the predicted values can adapt quickly to the delay variance in the acoustic channel.\",\"PeriodicalId\":378624,\"journal\":{\"name\":\"Proceedings of the 11th International Conference on Underwater Networks & Systems\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-10-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 11th International Conference on Underwater Networks & Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2999504.3001072\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 11th International Conference on Underwater Networks & Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2999504.3001072","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A new MAC based on RTT prediction for underwater acoustic networks
Most existing medium access control (MAC) protocols in underwater acoustic networks (UANs) ignore the delay variance that affects the estimation accuracy of round trip time (RTT). We predict the RTTs using Bayesian dynamic linear model. Using the predicted RTTs, we dynamically adjust the length of time slots in MAC. Experimental results show that the predicted values can adapt quickly to the delay variance in the acoustic channel.