Description: The Self-Stabilizing Consensus is a consensus algorithm designed to maintain consistency in distributed systems, even in the presence of transient failures. Its main feature is the ability to recover from these failures without external intervention, making it especially valuable in environments where availability and resilience are critical. This type of algorithm is based on the idea that nodes in a distributed system can reach an agreement on a common value, despite some of them experiencing temporary failures. This is achieved through the implementation of mechanisms that allow nodes to communicate and coordinate efficiently, ensuring that, despite interruptions, the system can restore its consensus state. Self-stabilization implies that the system can return to a correct operating state without manual intervention, reducing the need for constant monitoring and improving the overall robustness of the system. This approach is fundamental in applications where service continuity is essential, such as in sensor networks, distributed control systems, and cloud computing platforms, where failures can be common and the ability to recover quickly is crucial.
