In this paper, (CORN)2, a correlation-based, optimal sensing scheduling algorithm is developed for cognitive radio networks to minimize energy consumption. A sensing quality metric is defined as a measure of the correctness of spectral availability information. The optimal scheduling algorithm is shown to minimize the cost of sensing (e.g., energy consumption, sensing duration) while meeting the sensing quality requirements. To this end, (CORN)2 utilizes a novel sensing deficiency virtual queue concept and exploits the correlation between spectrum measurements of a particular secondary user and its collaborating neighbors. The proposed algorithm is further proved to achieve a distributed and optimal solution under certain, easily satisfied assumptions. In addition to the theoretically proved performance guarantees, the proposed algorithm is also evaluated through simulations.