Fatigue-aware management of cellular networks infrastructure with sleep modes

We consider the problem of controlling the rate of failures triggered by fatigue processes of Base Stations (BSs) in cellular networks subject to Sleep Modes (SMs). Specifically, the increase of time spent in SM tends to decrease the BS failure rate by following, e.g., the Arrhenius law. However, the transitions between the power states tend to increase the BS failure rate, which can be predicted by the Coffin- Manson model. In this context, the energy savings triggered by SMs would not be economically useful if the BS failure rate were increased too much. Our goal is therefore to tackle the problem of minimizing the BS failure rate in a cellular network subject to SMs. After showing that the optimal formulation of the problem is NP-Hard, we propose a new algorithm, named LIFE, to practically solve it. We run LIFE on different scenarios (driven by LTE and legacy UMTS technologies). Our results show that LIFE outperforms two previous energy-aware algorithms, which instead do not take into account the BS failure rate. Specifically, our solution is able to achieve up to 40% of power saving during night, without a strong penalty in the BS failure rate