optimising routing protocols for wireless sensor networks is a B.Tech project topic for Electronics & Communication Engineering. It gives students a clear starting point for research, implementation planning, and documentation.
optimising routing protocols for wireless sensor networks Project Details
| Abstract |
Wireless Sensor Networks (WSNs) have very limited energy, processing power, and bandwidth. Traditional routing protocols often cannot adjust quickly to changing conditions or node failures, which can cause the network to die early. This project looks at using AI methods—such as reinforcement learning and genetic algorithms—to improve routing in WSNs. By constantly checking parameters like remaining energy, link quality, and hop count, the AI‑based routing protocol picks the best cluster heads and transmission paths. The framework will be tested in simulations and compared with standard protocols such as LEACH and PEGASIS. Implementation will model node energy use, packet‑delivery ratio, and how much the network’s lifetime is extended. The guide helps
engineering students set up network topologies, add machine‑learning models for path selection, and evaluate performance metrics. The study provides a hands‑on way to see how smart decisions can reduce energy problems in distributed sensor networks and offers a clear path for design validation and performance comparison.
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| Reference Paper |
The Role of Artificial Intelligence in Optimising Routing Protocols for Wireless Sensor Networks |
| Domain |
Electronics & Communication Engineering |
| Sub-Domain |
Wireless Sensor Networks |
| PDF Download |
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| Get Help |
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