{"title":"Modeling Delay of Haptic Data in CSMA-based Wireless Multi-Hop Networks: A Probabilistic Approach","authors":"Frank Engelhardt, M. Günes","doi":"10.1109/PIMRCW.2019.8880820","DOIUrl":null,"url":null,"abstract":"The future Tactile Internet is expected to enable ultra-low-latency haptic communication in realtime between peers over arbitrary distances. This vision is currently highly based on the existing Internet Backbone and the upcoming 5G (and beyond) mobile communication networks. However, WiFi networks that are based on the IEEE 802.11 standard have spread widely and will be undiminishedly part of future networks. We derive a probabilistic model for estimation of latency in uncongested 802.11-based Wireless Multi-Hop Networks (WMHNs) with arbitrary topology. The model parameters are: (i) the data rate of the nodes, (ii) the packet error rate, (iii) the sending probability of the nodes, and (iv) the distribution of the queueing delay. In simulations our preliminary model can accurately predict both the minimum and maximum observed delays with multiple haptic flows present.","PeriodicalId":158659,"journal":{"name":"2019 IEEE 30th International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC Workshops)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 30th International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC Workshops)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PIMRCW.2019.8880820","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
The future Tactile Internet is expected to enable ultra-low-latency haptic communication in realtime between peers over arbitrary distances. This vision is currently highly based on the existing Internet Backbone and the upcoming 5G (and beyond) mobile communication networks. However, WiFi networks that are based on the IEEE 802.11 standard have spread widely and will be undiminishedly part of future networks. We derive a probabilistic model for estimation of latency in uncongested 802.11-based Wireless Multi-Hop Networks (WMHNs) with arbitrary topology. The model parameters are: (i) the data rate of the nodes, (ii) the packet error rate, (iii) the sending probability of the nodes, and (iv) the distribution of the queueing delay. In simulations our preliminary model can accurately predict both the minimum and maximum observed delays with multiple haptic flows present.