Literature DB >> 33302457

A Routing Algorithm Based on Real-Time Information Traffic in Sparse Environment for VANETs.

Jianhang Liu1, Fan Bai2, Haonan Weng2, Shibao Li2, Xuerong Cui2, Yucheng Zhang3.   

Abstract

Because of the specific characteristics, like high vehicular mobility, unstable topology, and interruption of inter-vehicle wireless communication, it is hard to make a perfect decision on packet forwarding in highly dynamic topology VANETs. Especially in a sparse urban environment, the poor connectivity of nodes will mostly cause problems such as data packet loss and routing redundancy. Therefore, how to choose the best relay node becomes a key challenge in the design of fast and reliable routing protocols. This paper presents real-time effective information traffic routing (RTEIT), which provides an optimal route for forwarding the data packets toward their destination when choosing the relay node. RTEIT introduces a new network parameter named effective information traffic which can estimate the connectivity of nodes by the path that has been successfully created. Moreover, for avoiding unexpected communication interruption, we propose a new formula to evaluate the status of the links via considering the speed, direction, and location information. Finally, the node utility, as the criterion of routing decision, is calculated by effective information traffic and link status. We use the simulator of SUMO and NS-3 platform to evaluate RTEIT, and the results are compared with GPSR MOPR, and MM-GPSR. The evaluation results demonstrate that RTEIT outperforms in terms of packet loss rate, end-to-end delay, and network yield.

Entities:  

Keywords:  connectivity; information traffic; routing protocol; vehicular ad hoc networks

Year:  2020        PMID: 33302457      PMCID: PMC7763438          DOI: 10.3390/s20247018

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  1 in total

1.  ECPC-ICP: A 6D Vehicle Pose Estimation Method by Fusing the Roadside Lidar Point Cloud and Road Feature.

Authors:  Bo Gu; Jianxun Liu; Huiyuan Xiong; Tongtong Li; Yuelong Pan
Journal:  Sensors (Basel)       Date:  2021-05-17       Impact factor: 3.576

  1 in total

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