Mobile cloud computing (MCC) can request the service of cloud from the mobile appliance, such as mobile phones, laptops, palm tops and so on for data transfer in such a way to provide more beneficial applications. The consumption of energy is a major problem during the transfer of data in MCC that is needed to be optimized with the allocation of the tasks to mobile or cloud environment in an efficient manner. In order to deal this issue, a hybrid particle-salp (PS-SALP) swarm optimization technique is proposed in this research that incorporates the characteristic features of the particles and the salps leading to better convergence to enhanced solution in the resource allocation of data transfer. The main aim of this paper is to minimize the utility cost (UC) representing a better balance between energy consumption and the period of execution of the task. Initially, the local optimal solutions for each problem is found, followed by which the global optimal solution is obtained using the proposed PS-SALP optimization algorithm. The performance of the proposed technique of data transfer in MCC is analyzed in terms of the metrics, such as UC, energy consumption, and the task execution time. The results show the superiority of the proposed technique in energy efficient data transfer in the MCC environment.