Routing Protocols Final Year Projects with Source Code

Byadmin Final Year Projects

Routing Protocols Final Year Projects for BE, BTech, ME, MSc, MCA and MTech final year engineering students. These Routing Protocols projects give practical experience and help complete final-year submissions. All projects follow IEEE standards and each project includes source code, project thesis report, presentation, project execution and explanation.

Routing Protocols Final Year Projects

  1. Location Centric Energy Harvesting Aware Routing Protocol for IoT in Smart Cities
    This project focuses on making IoT-based wireless sensor networks last longer by using energy harvesting. It introduces a simple way to route data between sensor nodes that uses less energy. The method chooses the best path based on the closest direction to the target node. Experiments show it works well and helps the network run efficiently for a longer time.
  2. A Fresh Look at Routing Protocols in Unmanned Aerial Vehicular Networks A Survey
    This project studies how drones communicate with each other while moving in the air. It explains why choosing the best path for sending data is difficult because drone networks change quickly. The work compares different new routing methods and shows how well they perform. It also highlights remaining challenges and areas for future research in drone communication.
  3. A Multi-Hop QoS-Aware and Predicting Link Quality Estimation PLQE Routing Protocol for Reliable WBSN
    This project uses small sensors placed on the body to collect important health data in real time. These sensors often lose connection because the body moves, which can delay or drop critical signals like ECG or EEG. The proposed method predicts the best communication path so the data reaches safely and on time. It improves reliability and reduces delays compared to existing methods.
  4. A Novel Mechanism for Misbehavior Detection in Vehicular Networks
    This project focuses on making smart traffic systems safer. It studies networks where vehicles communicate with each other and identifies unusual behavior that could signal attacks. The system detects these threats, blocks harmful vehicles, and keeps a record of suspicious activity. Tests show it works accurately with very few mistakes.
  5. An Efficient Approach for the Detection and Prevention of Gray-Hole Attacks in VANETs
    This project focuses on improving the security of vehicular networks, where vehicles communicate with each other for safety and traffic management. The researchers studied a type of cyberattack called Gray-Hole Attack, where malicious vehicles drop data packets. They proposed a new method to detect and prevent these attacks by monitoring unusual packet behavior. Simulations showed that their method improved data delivery, reduced delays, and performed better than existing approaches.
  6. Cluster-Based Protocol for Prioritized Message Communication in VANET
    This project focuses on improving communication in Vehicular Ad Hoc Networks (VANETs), which connect vehicles wirelessly. Traditional methods are often too slow for moving vehicles, especially for road safety alerts. The proposed approach uses a clustering method to send emergency messages faster. Non-urgent information is stored temporarily to ensure urgent messages reach vehicles without delay.
  7. ML-RPL Machine Learning-Based Routing Protocol for Wireless Smart Grid Networks
    This project uses machine learning to make wireless smart grid networks work better. It improves an existing routing protocol by predicting the best path for data to travel. The system helps data reach its destination more reliably and quickly. Tests show it delivers more packets with less delay, making the network more efficient.
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