A Visual-Information Based Forwarding Mechanism Incorporating Travel-Route-Aware Design in NDN-based VANETs
Author(s) -
Minh Ngo,
Satoshi Ohzahata,
Ryo Yamamoto
Publication year - 2025
Publication title -
ieee access
Language(s) - English
Resource type - Magazines
SCImago Journal Rank - 0.587
H-Index - 127
eISSN - 2169-3536
DOI - 10.1109/access.2025.3621522
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
Named Data Networking (NDN) has emerged as a promising solution to address high mobility and intermittent connectivity in vehicular ad hoc networks (VANETs). Originally, NDN-based methods use location-aware approaches to send packets to fixed destinations. However, with the rise of autonomous vehicles predefining travel-paths by navigation systems, maintaining information along these paths rather than traditional end-to-end location-aware methods has become increasingly critical. Conventional methods often struggle to support content retrieval at intermediate points along a travel-path or in scenarios with multiple concurrent content sources. To address these limitations, we propose Visual Information-based Forwarding (VIF) that leverages camera-based “see-to-send” forwarding, and integrates a travel-route-aware naming scheme within the NDN architecture. To improve routing at junctions, we introduce the deployment of assistance nodes at junctions that relay packets along designated paths, thereby reducing the broadcast redundancy. In addition, we emphasize the importance of addressing post-emergency congestion, which arises when vehicles are positioned at a considerable distance from an emergency area and move toward the affected region. This challenge is mitigated by leveraging VIF’s proactive travel-route-awareness to reduce potential congestion. Finally, we validated the effectiveness of VIF through extensive simulations across various traffic scenarios, using the content delivery ratio as the primary metric.
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