In this paper we evaluate our own weak consistency algorithm, which is called the ”Fast Consistency Algorithm”, and whose main aim is optimizing the propagation of changes introducing a preference for nodes and zones of the network which have greatest demand. Weak consistency algorithms allow us to propagate changes in a large, arbitrary changing storage network in a self-organizing way. These algorithms generate very little traffic overhead; they have low latency and are scalable, in addition to being fault tolerant. The algorithm has been simulated over ns-2, and measured its performance for complex spatial distributions of demand, including Internet like self-similar fractal distributions of demand. The impulse response of the algorithm has been characterized. We conclude that considering application parameters such as demand in the event or change propagation mechanism to: 1) prioritize probabilistic interactions with neighbors with higher demand, and 2) including little changes on the logical topology (leader interconnection in hierarchical topology ), gives a surprising improvement in the speed of change propagation perceived by most users. In other words, it satisfies the greatest demand in the shortest amount of time.