A Multi-Agent-Based Approach for Semantic Conformance and Interoperability Testing in IoV Environments

Area of Science:

• Computer Science
• Network Engineering
• Artificial Intelligence

Background:

• Internet of Vehicles (IoV) implementation requires robust testing for device availability, communication reliability, quality of service, and security.
• Challenges in IoV testing include system dynamics, component heterogeneity, and large data streams from distributed elements.
• Ensuring seamless interaction and coherence among diverse IoV components is a significant hurdle.

Purpose of the Study:

• To propose an intelligent agent-based architecture specifically designed for semantic interoperability testing in IoV systems.
• To enhance the interaction and coherence between heterogeneous components within IoV-based systems.
• To address the complexities of testing dynamic and distributed IoV environments.

Main Methods:

• Development of an intelligent agent-based architecture focused on semantic interoperability.
• Implementation of the proposed architecture within the NetLogo multi-agent simulation environment (v6.4.0).
• Application of the architecture to a case study for detecting semantic interoperability issues.

Main Results:

• The proposed architecture successfully detects semantic interoperability issues within the IoV system.
• Issues were identified at both the data and query levels, validating the architecture's effectiveness.
• The agent-based approach demonstrated feasibility in a simulated IoV environment.

Conclusions:

• The intelligent agent-based architecture offers a viable solution for semantic interoperability testing in IoV.
• This approach improves the coherence and interaction of distributed IoV components.
• The study validates the effectiveness of semantic interoperability testing for enhancing IoV system reliability.