A Survey and Tutorial on Network Optimization for Intelligent Transport System Using the Internet of Vehicles

Area of Science:

• Computer Science
• Electrical Engineering
• Transportation Engineering

Background:

• The Internet of Things (IoT) has evolved significantly, leading to the emergence of the Internet of Vehicles (IoV) as a key trend.
• IoV enables the development of Intelligent Transportation Systems (ITS), but faces challenges due to massive data transfer overheads.
• Network connectivity optimization is crucial for efficient ITS performance within IoV environments.

Purpose of the Study:

• To present a comprehensive survey on network optimization techniques within IoT and IoV contexts.
• To highlight the evolution and applications of IoT and IoV, particularly in ITS.
• To categorize relevant algorithms and introduce simulation tools for IoV research.

Main Methods:

• Literature review and synthesis of existing research on IoT and IoV network optimization.
• Comparative analysis of different advancements and applications in ITS.
• Categorization of network optimization algorithms and discussion of simulation tools.

Main Results:

• Identification of network connectivity overheads as a major challenge in IoV for ITS.
• Overview of current advancements and applications in IoT and IoV, with a focus on ITS.
• A structured categorization of network optimization algorithms and a review of simulation tools.

Conclusions:

• Network optimization is essential for realizing efficient and scalable Intelligent Transportation Systems through the Internet of Vehicles.
• The study provides a valuable resource for researchers by consolidating information on IoV, ITS, optimization techniques, and tools.
• Further research utilizing the discussed simulation tools can advance the field of IoV network optimization.