Enhancing Fault Tolerance in Wireless Mesh Networks through Adaptive and Resilient Routing Protocols

From smart cities to disaster response systems, Wireless Mesh Networks (WMNs) are an essential component of many different kinds of infrastructure. Their great sensitivity to different types of errors, however, makes it very difficult to maintain trustworthy communication. The goal of this research is to improve WMN fault tolerance by developing new resilient and adaptive routing algorithms. The main goal is to detect faults in real-time using dynamic algorithms that can detect and react to disturbances including link failures, node unavailability, and changes in the environment. On top of that, the research suggests adaptive routing algorithms that may respond to changing network conditions, improve communication pathways, and avoid broken parts. In the meanwhile, we look at resilient topology control methods, which stress the need to keep a strong network architecture with features like redundancy, load balancing, and quick adaptability to topological changes.This research takes a novel tack by combining machine learning models for fault prediction and proactive repair. These models add to a predictive fault-tolerance paradigm by using network patterns and historical data, which further strengthens the network’s resilience. Included in the thorough evaluation of the protocols created in this paper are simulations and real experiments. These evaluations cover important performance metrics like latency, throughput, and overall network reliability. The study reveals the suggested protocols’ strengths and weaknesses by a thorough comparison with current fault-tolerant routing methods. By laying the groundwork for resilient and adaptive fault-tolerant communication in complex and ever-changing contexts, the results ultimately help wireless mesh networks progress.