Papers accepted: Efficient Location-Based Service Discovery for IoT and Edge Computing in the 6G Era & Enhancing Traffic Safety with AI and 6G: Latency Requirements and Real-Time Threat Detection

Efficient Location-Based Service Discovery for IoT and Edge Computing in the 6G Era

Authors: Kurt Horvath, Dragi Kimovski

Conference: 2025 10th International Conference on Information and Network Technologies (ICINT 2025)

Abstract: Efficient service discovery is a cornerstone of the rapidly expanding Internet of Things (IoT) and edge computing ecosystems, where low latency and localized service provisioning are critical. This paper proposes a novel location-based DNS (Domain Name System) method that leverages Location Resource Records (LOC RRs) to enhance service discovery. By embedding geographic data in DNS responses, the system dynamically allocates services to edge nodes based on user proximity, ensuring reduced latency and improved Quality of Service (QoS). Comprehensive evaluations demonstrate minimal computational overhead, with processing times below 1 ms, making the approach highly suitable for latency-sensitive applications. Furthermore, the proposed methodology aligns with emerging 6G standards, which promise sub-millisecond latency and robust connectivity. Future research will focus on real-world deployment, validating the approach in dynamic IoT environments. This work establishes a scalable, efficient, and practical framework for location aware service discovery, providing a strong foundation for next generation IoT and edge-computing solutions.

 

Enhancing Traffic Safety with AI and 6G: Latency Requirements and Real-Time Threat Detection

Authors: Kurt Horvath, Dragi Kimovski, Stojan Kitanov, Radu Prodan

Conference: 2025 10th International Conference on Information and Network Technologies (ICINT 2025)

Abstract: The rapid digitalization of urban infrastructure opens the path to smart cities, where IoT-enabled infrastructure enhances public safety and efficiency. This paper presents a 6G and AI-enabled framework for traffic safety enhancement, focusing on real-time detection and classification of emergency vehicles and leveraging 6G as the latest global communication standard. The system integrates sensor data acquisition, convolutional neural network-based threat detection, and user alert dissemination through various software modules of the use case. We define the latency requirements for such a system, segmenting the end-toend latency into computational and networking components. Our empirical evaluation demonstrates the impact of vehicle speed and user trajectory on system reliability. The results provide insights for network operators and smart city service providers, emphasizing the critical role of low-latency communication and how networks can enable relevant services for traffic safety.