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Research in the wireless sensor networks field has been plagued by difficulties in realistic simulations. These difficulties are often the result of non-realistic assumptions which need to be removed from the mathematical models. Especially, radio propagation models are often simplified and do not take into consideration irregularities such as fading, shadowing, and temporal non-stationarity. In this paper, we investigate the effect of radio temporal irregularities on sensor deployment and sleep scheduling. We show that existing scheduling algorithms suppose that the sensor coverage range does not vary according to time, which is not true because the available energy decreases. We analyze the impact of this shortcoming on the performance of sleep scheduling algorithms and propose an alternative scheme that guarantees a uniform density distribution despite of the presence of radio temporal irregularities.