Nowadays, cloud computing is growing rapidly and has been developed as an adequate and adaptable paradigm in solving large-scale problems. Since the number of cloud users and their requests are increasing fast, the loads on the cloud data center may be under-loaded or over-loaded. These circumstances induce various problems, such as high response time and energy consumption. High energy consumption in the cloud data center has drastic negative impacts on the environment. Literature shows that scheduling plays a significant role in the reduction of energy consumption. In the recent decade, this problem has attracted huge interest among researchers, and several solutions have been proposed. Energy-efficient service (task) allocation with high Customer Satisfaction (CS) constraint has become a critical problem of a cloud. In this paper, a high CS-based energy-efficient service allocation framework has been designed. This optimizes the energy consumption as well as the CS level in the cloud. The proposed algorithm is simulated in CloudSim simulator and compared with some standard algorithms. The simulation results show in favor of the proposed algorithm.