In cognitive radio sensor networks, one of the fundamental tasks is cooperative spectrum sensing by multiple cognitive radio (CR) sensors to improve the spectrum detection performance. However, during each cooperative sensing process, extra energy is consumed by the selected sensors through local sensing, data reporting, and data fusion activities. Thus, cooperative sensing processes call for energy efficiency. This paper investigates two practical optimization problems related to energy efficient cooperative sensing issue. One focuses on the sensors selection in a single process, with the objective to minimize the total energy consumption meanwhile the expected sensing performances are achieved. The other is an online problem, which schedules participant sensors for each process with the aim to enable the network to perform as many as cooperative sensing processes, therefore increasing the network lifetime. Due to the NP-hardness of the proposed problems, we propose heuristic algorithms for them respectively. Extensive experiments by simulations demonstrate the effectiveness of the proposed algorithms. Using the proposed algorithms, more cooperative sensing processes can be realized and the network lifetime can be extended significantly.