Attributes Based Vehicular Named Data Networking for Driving Assistance

IF 6.7 2区计算机科学 Q1 ENGINEERING, MULTIDISCIPLINARY

IEEE Transactions on Network Science and Engineering Pub Date : 2025-03-11 DOI:10.1109/TNSE.2025.3550154

Xiaonan Wang;Gaoyang Wu

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引用次数: 0

Abstract

The Named Data Networking (NDN) provides an efficient data delivery paradigm, so it is introduced to vehicular environments, called the Vehicular Named Data Networking (VNDN), to enhance efficiency of vehicular data dissemination. NDN only provides the pull-based data delivery mode, but vehicular data is required to be transmitted in both push and pull modes. Moreover, the caching-everything-everywhere strategy employed by NDN is inefficient in vehicular scenarios because vehicles have limited storage resources. Taking these issues into account, we propose an attributes based vehicular named data networking framework, and aim to reduce data dissemination latency and overheads. The main idea behind the framework is to exploit vehicle attributes and relationships between routes and vehicular data to enhance stability of persistent paths and efficiency of in-network caching, ultimately achieving rapid data dissemination. The experiment results demonstrate the superiority of the framework in terms of data dissemination latency, overheads and success rates.

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基于属性的车辆命名数据网络驾驶辅助

命名数据网络（NDN）提供了一种高效的数据传输模式，因此将其引入车载环境，称为车载命名数据网络（VNDN），以提高车载数据传播的效率。NDN只提供基于拉的数据传输方式，而车载数据需要同时采用推拉两种传输方式。此外，由于车辆的存储资源有限，NDN采用的缓存所有内容的策略在车辆场景中效率很低。考虑到这些问题，我们提出了一个基于属性的车辆命名数据网络框架，旨在减少数据传播延迟和开销。该框架的主要思想是利用车辆属性以及路径和车辆数据之间的关系，增强持久路径的稳定性和网络内缓存的效率，最终实现数据的快速传播。实验结果表明，该框架在数据传播延迟、开销和成功率方面具有优势。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Transactions on Network Science and Engineering Engineering-Control and Systems Engineering

CiteScore

12.60

自引率

9.10%

发文量

393

期刊介绍： The proposed journal, called the IEEE Transactions on Network Science and Engineering (TNSE), is committed to timely publishing of peer-reviewed technical articles that deal with the theory and applications of network science and the interconnections among the elements in a system that form a network. In particular, the IEEE Transactions on Network Science and Engineering publishes articles on understanding, prediction, and control of structures and behaviors of networks at the fundamental level. The types of networks covered include physical or engineered networks, information networks, biological networks, semantic networks, economic networks, social networks, and ecological networks. Aimed at discovering common principles that govern network structures, network functionalities and behaviors of networks, the journal seeks articles on understanding, prediction, and control of structures and behaviors of networks. Another trans-disciplinary focus of the IEEE Transactions on Network Science and Engineering is the interactions between and co-evolution of different genres of networks.