The scaling exponent is independent of m, the only parameter in the model. Since the power law observed for real networks describes systems of rather dierent sizes at dierent stages of their development, one expects that a correct model should provide a distribution whose main features are independent of time. Indeed, as Fig. 4b demonstrates, P(k) is independent of time (and, subsequently, independent of the system size N = m0 + t), indicating that despite its continuous growth, the system organizes itself into a scale-free stationary state