The purpose of using Cloudlet is remotely reducing the cloud communication delay and the system load. Still, since the prevailing system performance of the remote cloud is not in the cloudlet, as the no. of users changes, the cloud provides resources for each user change. Moreover, as the cloudlet's service security is low, the cloudlet's service for users is eliminated from coverage when work activation. In this circumstance, users will not get the computational results, so cloud computing fails. This work offers a real-time resource allocation framework for users to allocate sufficient and necessary resources. This work proposes the Movement Record-Oriented Particle Swarm Optimization (MROPSO) method to unravel the issue of work failure and real-time resource allocation. The method proposed by this paper provides a better powerful result than the real PSO method.