In the domain of cloud based mobile computing, efficient processing of applications require lightweight methods owing to the resource constraints in mobile platforms. The strength of the wireless communication signal, which varies with the distance between the wireless node and mobile station, is necessary for adapting to the mobile computing environment. This study implements a Buffering control logic process that utilizes mobility speed velocity and wireless signal node strength to compute the radio frequency of mobile stations (FMS), which determines how frequently a wireless terminal re-enters an area with a stronger connectivity signal. The study employs the OMNeT++ simulator tool to evaluate network-driven performance metrics, such as payload size, Network hops, load shifts at access points, buffer fill rate, and buffer playback ratio, while also examining the effects of dynamic workload changes on physical servers. The proposed BD process determines the FMS to ascertain the optimal data buffering rate, thereby ensuring consistent application response level during migration. Key findings reveal a drop in packet delivery ratio as the number of users increases (from 0.99 for two users to 0.62 for 25 users), an exponential increase in transition period (from 68.24 s for 0 users to 413.51 s for 25 users), and a decrease in buffering speed as the frequency of increase in mobile modes (from 400 bits/s at 1.25 frequency to 100 bits/s at 5.0 frequency). The access point capacity is federated either symmetrically or asymmetrically among users, with unequal sharing benefiting certain users. This research emphasizes the significance of mobile-driven strategies in MCC for Supporting optimal operation under dynamic conditions and offers deep awareness into optimizing buffering fill rates and load distribution. Future research directions include integrating machine learning for dynamic buffering fill rate prediction and broadening the study to other network landscapes. The findings can improve mobile application functionality in actual scenarios, such as university networks, company intranets, and free Wi-Fi hotspots, ensuring smoother user experiences even in traffic intensive situations.