{"title":"Connected vehicles under information-centric architectures","authors":"M. Tavan, R. Yates, D. Raychaudhuri","doi":"10.1109/VNC.2016.7835963","DOIUrl":"https://doi.org/10.1109/VNC.2016.7835963","url":null,"abstract":"Fast changing topologies, unpredictable network loads, potential broadcast storms, and identity-location conflation problems in IP networks all impose challenges on connected car system design. Prior approaches have proposed smart flooding using location information, carry and forward, and GeoServer assisted algorithms. Due to the complexity and overhead imposed by these approaches, their applications are restricted to local information transfer, dissemination of popular content, or delay-tolerant scenarios. In this work, we propose FastMF to extend both accessibility of the Internet for vehicular nodes and reachability of vehicular nodes from any remote server. Furthermore, by forming clusters of vehicles with similar mobility patterns, leveraging cluster to infrastructure links, and maintaining the mapping between node IDs and network addresses in a logically centralized server, we provide the nodes without a direct Internet connection with the benefit of an indirect association to an Internet gateway. Results from NS3 experiments illustrate the improvements in throughput for downloading large files derived by clustering and multi-hop transfer of data. In addition, experiments with interactive web-browsing scenarios indicate a significant improvement in delay in various mobility scenarios.","PeriodicalId":352428,"journal":{"name":"2016 IEEE Vehicular Networking Conference (VNC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114178707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Poster: A scheduling method for V2V networks using successive interference cancellation","authors":"Yuta Watanabe, Koya Sato, T. Fujii","doi":"10.1109/VNC.2016.7835947","DOIUrl":"https://doi.org/10.1109/VNC.2016.7835947","url":null,"abstract":"In this paper, we propose a scheduling method with successive interference cancellation (SIC) for vehicle to vehicle (V2V) networks to improve the reliability and the capacity. SIC is a multi-user detection technique that repeatedly decodes the multiple signals by cancelling the strongest signal by using the detected signal in the previous step. In the proposed distributed scheduling method, the time slots are allocated by using the location information of the vehicles and the estimated signal to interference plus noise ratio (SINR) at multiple receivers for effectively working SIC. The location information can be known by the iterative beacon signal transmitted from each vehicles. The proposed method enables simultaneous detection by SIC. We compare the performance of the proposed scheduling method with random allocation method under multiple peer to peer unicast communication. In addition, we set SINR margin to slot allocation for improving robustness of SIC.","PeriodicalId":352428,"journal":{"name":"2016 IEEE Vehicular Networking Conference (VNC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124348144","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
R. Meng, David Wolfgang Gromling, Romit Roy Choudhury, Srihari Nelakuditi
{"title":"RideSense: Towards ticketless transportation","authors":"R. Meng, David Wolfgang Gromling, Romit Roy Choudhury, Srihari Nelakuditi","doi":"10.1109/VNC.2016.7835965","DOIUrl":"https://doi.org/10.1109/VNC.2016.7835965","url":null,"abstract":"Imagine a transportation system in which passengers simply get on/off without any explicit ticketing operation. Yet, the system tracks usage and charges passengers. Such a system will not only be more convenient and efficient, but also be more conducive for analytics, than existing systems. Towards that goal, we exploit the opportunity that people are carrying sensor-equipped smart devices, and their motion trajectories/patterns and experienced environment can be measured continuously. Assuming that vehicles are also equipped with such sensors (perhaps fixed devices or smart devices carried by drivers), the vehicles' motion and the experienced environment characteristics can also be recorded and uploaded to cloud. Under these assumptions, we hypothesize that the motion/environment sensed by a passenger's smart device correlates strongly with that of the vehicle she is traveling in and is distinct from that of other vehicles and/or other traces of the same vehicle. In this paper, we expand on this intuition and develop a system, called RideSense, that matches a passenger's sensor trace against the traces of buses in that area, to determine which bus, when she has taken and where she gets on/off. Our evaluation of RideSense, with 20+ hours of traces from 5 bus lines in our area, shows that it achieves an accuracy of 84∼98%, depending on the choice of sensors and their features, positions of the passengers' phones and the metrics of measurement. These results, while far from conclusive, offer confidence that ticketless public transportation may indeed be a possibility in smart cities of the future.","PeriodicalId":352428,"journal":{"name":"2016 IEEE Vehicular Networking Conference (VNC)","volume":"220 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131553150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Thierry Derrmann, S. Faye, Raphaël Frank, T. Engel
{"title":"Poster: LuST-LTE: A simulation package for pervasive vehicular connectivity","authors":"Thierry Derrmann, S. Faye, Raphaël Frank, T. Engel","doi":"10.1109/VNC.2016.7835952","DOIUrl":"https://doi.org/10.1109/VNC.2016.7835952","url":null,"abstract":"Recent technological advances in communication technology have provided new ways to understand human mobility. Connected vehicles with their rising market penetration are particularly representative of this trend. They become increasingly interesting, not only as sensors, but also as participants in Intelligent Transportation System (ITS) applications. More specifically, their pervasive connectivity to cellular networks enables them as passive and active sensing units. In this paper, we introduce LuST-LTE, a package of open-source simulation tools that allows the simulation of vehicular traffic along with pervasive LTE connectivity.","PeriodicalId":352428,"journal":{"name":"2016 IEEE Vehicular Networking Conference (VNC)","volume":"194 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115982539","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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