The Internet of Things and 5G technologies have made mobile cloud computing emerge and develop rapidly. However, the rapid development of mobile applications requires cloud computing to have lower network latency and computing energy consumption. Therefore, Mobile edge computing (MEC) which is a promising technology has received widespread attention. Nowadays, it is important to schedule resources reasonably due to the communication and computing resources shortage. In this paper, we propose a mobile edge computing task scheduling algorithm in a multi-user multi-tasking environment. The algorithm takes into account the time sensitivity of mobile applications. We optimize the traditional task scheduling algorithm with the user's minimum average execution time and minimum computing energy consumption as the goals. Extensive experiments are carried out on MATLAB. The result shows that our proposed algorithm can effectively reduce the time and energy cost of mobile edge computing.