As a low-cost and high-performance distributed computing platform, user-PC computing (UPC) system has been studied based on the master-worker model. It uses idling resources of personal computers (PCs) of users for workers. Docker containers are introduced to run the jobs of applications programs on various PC environments. Previously, the UPC system only accepts jobs from users manually using the web interface. In this paper, we implement two online job acceptance functions in the UPC system using Secure Shell File Transfer Protocol (SFTP) and a cloud storage, so that application systems can submit jobs and receive results online. For evaluations, we adopt Android programming learning assistance system (APLAS) and Exercise and performance learning assistant system (EPLAS) as the application systems, which have been developed in our group, and pCloud for the cloud storage. The experiment results show that the total CPU time is reduced by 90.5% for APLAS and 55.1% for EPLAS of the original, respectively.