With the recent explosion in mobile data, the energy consumption and carbonfootprint of the mobile communications industry is rapidly increasing. It iscritical to develop more energy-efficient systems in order to reduce thepotential harmful effects to the environment. One potential strategy is toswitch off some of the under-utilized base stations during off-peak hours. Inthis paper, we propose a binary Social Spider Algorithm to give guidelines forselecting base stations to switch off. In our implementation, we use a penaltyfunction to formulate the problem and manage to bypass the large number ofconstraints in the original optimization problem. We adopt several randomlygenerated cellular networks for simulation and the results indicate that ouralgorithm can generate superior performance.
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