Smart downlink scheduling can be used to reduce infrastructure-to-vehicle energy costs in delay tolerant roadside networks. In this thesis this type of scheduling is incorporated into ON/OFF roadside unit sleep activity, to further reduce infrastructure power consumption. To achieve significant power savings however, the OFF-to-ON sleep transitions may be very lengthy, and this overhead must be taken into account when performing the scheduling. The OFF/ON sleep transitions are incorporated into a lower bound on energy use for the constant bit rate air interface case. An online scheduling algorithm referred to as the Flow Graph Sleep Scheduler (FGS) is then introduced which makes locally optimum ON/OFF cycle decisions. This is done by computing energy estimates needed both with and without a new OFF/ON cycle. The energy calculation can be efficiently done using a novel minimum ow graph formulation. We also consider the fixed transmit power, variable bit rate, air interface case. As before, a lower bound on RSU energy use is computed by formulating and solving an integer program. Results from a variety of experiments show that the proposed scheduling algorithms perform well when compared to the energy lower bounds. The algorithms are especially attractive in situations where vehicle demands and arrival rates are such that the energy costs permit frequent ON/OFF cycling.