This paper presents the description, practical implementation, and stability analysis of a recently proposed, energy-efficient, medium access control protocol for wireless sensor networks, ALOHA-Q, which employs a reinforcement-learning framework as an intelligent transmission strategy. The channel performance is evaluated through a simulation and experiments conducted using a real-world test-bed. The stability of the system against possible changes in the environment and changing channel conditions is studied with a discussion on the resilience level of the system. A Markov model is derived to represent the system behavior and estimate the time in which the system loses its operation. A novel scheme is also proposed to protect the lifetime of the system when the environment and channel conditions do not sufficiently maintain the system operation.
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