Constraints on the energy, bandwidth, and connectivity of mobile devices and wireless communication medium complicate the timely and reliable access to public data. Energy is often the most stringent constraint, necessitating techniques that facilitate operation in energy-saving modes. Broadcasting, typically over parallel channels, has proven to be an effective method for dissemination of public data to mobile devices. However, the employment of parallel channels introduces challenges associated with channel switching and conflicts due to concurrent accesses to multiple data items that ultimately increase energy consumption and response time. The detrimental effects on energy consumption and response time can be alleviated by scheduling the retrieval of data items in an order that reduces the number of passes over the air channels and channel switching between the parallel channels. In this paper, several scheduling algorithms are proposed and analyzed that achieve the aforementioned objectives. To further improve energy consumption and response time, the scope of our scheduling algorithms has been enhanced by replication of popular data items. The proposed scheduling algorithms, both with and without replication, have been simulated, and simulation results are presented and analyzed. These results show that the proposed scheduling algorithms, compared to some heuristic based methods, have greater impact in reducing energy consumption and response time. This reduction is shown to be more pronounced with replication of data items.