Moisture Computing-Based Internet of Vehicles (IoV) Architecture for Smart Cities

Area of Science:

• Computer Science
• Network Engineering
• Transportation Systems

Background:

• The Internet of Vehicles (IoV) leverages interconnected smart vehicles for diverse services.
• Current edge and cloud computing architectures in IoV face challenges like high latency and infrastructure costs.

Purpose of the Study:

• To introduce moisture computing (MC) as a novel architecture for IoV.
• To address the limitations of edge and cloud computing in IoV environments.
• To enhance traffic monitoring, road safety, and emergency response services in IoV.

Main Methods:

• Proposed a moisture computing (MC) architecture deployed between edge and cloud.
• Conducted mathematical analyses to evaluate network delays and response times.
• Performed simulation-based implementation to assess computational performance.

Main Results:

• MC architecture demonstrated reduced network delays and improved response times compared to edge and cloud computing.
• Mathematical analyses confirmed the efficiency of MC in minimizing delays.
• Simulation results indicated optimized total processing time, with minimized computation and communication delays.

Conclusions:

• Moisture computing (MC) offers an efficient solution for IoV, outperforming traditional edge and cloud approaches.
• MC effectively reduces infrastructure costs through medium-scale data centers.
• The proposed MC architecture enhances smart vehicle collaboration for improved traffic management and safety.