{"title":"基于时间的VANETs变速数据转发决策","authors":"Jensen Hung, R. E. Grande","doi":"10.1109/DCOSS49796.2020.00039","DOIUrl":null,"url":null,"abstract":"Vehicular Clouds heavily rely on the underlying Vehicular Networks to discover, announce, and exchange services and resources. The assembly and control of such clouds depend upon reliable and efficient data dissemination among vehicles and roadside units. Dissemination allows for critical information to be spread efficiently and widely through the VANETs. It is, therefore, imperative to create a dissemination algorithm that reduces the number of redundant messages. The biggest concern is to define an effective and efficient data dissemination algorithm that can be used in critical areas in traffic like intersections. Several issues must be considered in dense vehicular regions, such as broadcast storms and redundancy. Several approaches have already shown a reduction in the redundancy and overhead. Still, they may need to improve on the variance of a dynamically changing topology and exponential growth rate of messages sent. These approaches include a speed adaptive probabilistic dissemination, which is a lightweight approach. This work focuses on controlling the dissemination pace by applying timers and limiting forwarding messages on the speed adaptive broadcast algorithm to reduce overhead and redundancy while ensuring the broadcast is transmitted evenly. The timers are useful in high-density traffic and conclusively showed a broadcast overhead reduction.","PeriodicalId":198837,"journal":{"name":"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"127 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Timer-based Decision in Speed-Variant Data Forwarding for VANETs\",\"authors\":\"Jensen Hung, R. E. Grande\",\"doi\":\"10.1109/DCOSS49796.2020.00039\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Vehicular Clouds heavily rely on the underlying Vehicular Networks to discover, announce, and exchange services and resources. The assembly and control of such clouds depend upon reliable and efficient data dissemination among vehicles and roadside units. Dissemination allows for critical information to be spread efficiently and widely through the VANETs. It is, therefore, imperative to create a dissemination algorithm that reduces the number of redundant messages. The biggest concern is to define an effective and efficient data dissemination algorithm that can be used in critical areas in traffic like intersections. Several issues must be considered in dense vehicular regions, such as broadcast storms and redundancy. Several approaches have already shown a reduction in the redundancy and overhead. Still, they may need to improve on the variance of a dynamically changing topology and exponential growth rate of messages sent. These approaches include a speed adaptive probabilistic dissemination, which is a lightweight approach. This work focuses on controlling the dissemination pace by applying timers and limiting forwarding messages on the speed adaptive broadcast algorithm to reduce overhead and redundancy while ensuring the broadcast is transmitted evenly. The timers are useful in high-density traffic and conclusively showed a broadcast overhead reduction.\",\"PeriodicalId\":198837,\"journal\":{\"name\":\"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)\",\"volume\":\"127 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DCOSS49796.2020.00039\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DCOSS49796.2020.00039","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Timer-based Decision in Speed-Variant Data Forwarding for VANETs
Vehicular Clouds heavily rely on the underlying Vehicular Networks to discover, announce, and exchange services and resources. The assembly and control of such clouds depend upon reliable and efficient data dissemination among vehicles and roadside units. Dissemination allows for critical information to be spread efficiently and widely through the VANETs. It is, therefore, imperative to create a dissemination algorithm that reduces the number of redundant messages. The biggest concern is to define an effective and efficient data dissemination algorithm that can be used in critical areas in traffic like intersections. Several issues must be considered in dense vehicular regions, such as broadcast storms and redundancy. Several approaches have already shown a reduction in the redundancy and overhead. Still, they may need to improve on the variance of a dynamically changing topology and exponential growth rate of messages sent. These approaches include a speed adaptive probabilistic dissemination, which is a lightweight approach. This work focuses on controlling the dissemination pace by applying timers and limiting forwarding messages on the speed adaptive broadcast algorithm to reduce overhead and redundancy while ensuring the broadcast is transmitted evenly. The timers are useful in high-density traffic and conclusively showed a broadcast overhead reduction.