An optimized location service for the fifth generation VANETs inspired by traffic lights

Area of Science:

• Vehicular Ad-Hoc Networks (VANETs)
• Wireless Communication Systems
• Network Localization

Background:

• Vehicular ad-hoc networks (VANETs) are crucial for public emergency applications, requiring real-time vehicle localization.
• Existing localization services face challenges like network disconnection and overloading in dynamic 5G VANET environments.
• 5G VANETs offer low latency, supporting time-sensitive applications.

Purpose of the Study:

• To propose an optimized localization service for 5G VANETs inspired by traffic light signaling.
• To enhance real-time vehicle localization for efficient message delivery in emergency scenarios.
• To address the limitations of existing localization techniques in dynamic network topologies.

Main Methods:

• A novel Traffic Light-Inspired Location Service (TLILS) is introduced.
• Roadside Units (RSUs) are utilized as location servers, selected based on maximum traffic weight metrics.
• Traffic weight metrics incorporate vehicle speed, connection time, and neighbor density.

Main Results:

• The proposed TLILS demonstrates superior performance compared to Name-ID Hybrid Routing (NIHR) and Zoom-Out Geographic Location Service (ZGLS).
• TLILS achieved a high Packet Delivery Ratio (PDR) of 0.96.
• TLILS recorded the shortest end-to-end delay, measuring 0.001 seconds.

Conclusions:

• The TLILS effectively manages vehicle localization in 5G VANETs, outperforming existing methods.
• This approach significantly improves packet delivery and reduces latency for critical VANET applications.
• TLILS offers a robust solution for real-time localization challenges in rapidly evolving vehicular networks.