Abstract

Vehicular ad-hoc networks (VANETs) address a steadily expanding demand, particularly for public emergency applications. Real-time localization of destination vehicles is important for determining the route to deliver messages. Existing location administration services in VANETs are classified as flooding-based, flat-based, and geographic-based location services. Existing localization techniques suffer from network disconnection and overloading because of 5G VANET topology changes. 5G VANETs have low delay and support time-sensitive applications. A traffic light-inspired location service (TLILS) is proposed to manage localization inspired by traffic lights. The proposed optimized localization service uses roadside units (RSUs) as location servers. RSUs with the maximum traffic weight metrics were chosen. Traffic weight metrics are based on speed of vehicles, connection time and density of neighboring vehicles. The proposed TLILS outperforms both Name-ID Hybrid Routing (NIHR) and Zoom-Out Geographic Location Service (ZGLS) for packet delivery ratio (PDR) and delay. TLILSs guarantee the highest PDR (0.96) and the shortest end-to-end delay (0.001 s) over NIHR and ZGLS.

Highlights

  • Owing to their continually increasing demand, for public emergency applications, Vehicular ad-hoc networks (VANETs) are an interesting area of investigation

  • Name-ID Hybrid Routing (NIHR) relayed on limited flooding and did not rely on a location service required by other protocols proposed for VANETs [20]

  • traffic light-inspired location service (TLILS) is placed at the intersection which is inspired by traffic lights

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Summary

Introduction

Owing to their continually increasing demand, for public emergency applications, VANETs are an interesting area of investigation. Because the topology varies in VANETs, the position, speed of vehicles, and road type should be considered to provide location information [5]. Scalable location services are important for covering all types of roads, including primary roads and subways. Road-side units are utilized in our proposed location service to cover four directions at the intersections. Scalability was supported using roadside units covering four directions at the intersections. Traffic lights serve both types of roads, the main road which that has four directions, and the subway which contains four directions. Our well-distributed location service in the four road directions enables location information distribution, precise results of vehicle locations, and small overheads. We tested our traffic-light-inspired location administration service by varying the number of vehicles and their speeds.

Related works
Optimized 5G traffic-based TLILS choice
TLILS search
22: Remove S
Simulation model
Simulation’s metrics
Simulation scenarios
Experimental results
Conclusion
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