AI-Driven Handover Optimization in VANETs (PhD proposal)

As the applicant for this project, my primary goal is to optimize resource allocation within Vehicular Ad Hoc Networks (VANETs) through the application of Artificial Intelligence (AI). Specifically, the project will involve implementation of Machine Learning techniques to make handover decisions, with the potential to significantly improve network efficiency and reliability of communication. Key Responsibilities: • Develop Machine Learning models tailored to VANET handover decisions. • Analyze both simulated and real-world vehicle data. • Optimize resource allocation strategies based on the Machine Learning insights. Skills and Experience Required: • Proficiency in Machine Learning methodologies and algorithms. • Familiarity with VANETs, vehicular communications, and handover decisions. • Experience in working with both simulated and real-world vehicular data. • Strong analytical skills for data interpretation and trend detection. The required is as follows: 1. Write a PhD proposal, the references (cited works) must be from Q1,Q2 journals. 2. The number of related work must be at least 70 references. 3. The work must be submitted after the proof reading and similarity index have been made. 4. For each reference has been selected, the selection reason should be clarified and the entire work must be clear (pros and cons). 5. The proposal must come with 3 clear objectives. 6. Methodology must be described in the proposal.