<p>The enormous growth of cloud technology and widespread use of smartphones in recent years has led to the development of many applications for video downloading and streaming. The two major challenges faced during the continuous video streaming from the cloud to mobile devices are low bandwidth and congestion. This led to poor-quality video delivery in mobile networks. To enhance the performance of mobile cloud networks, we propose new algorithms that will estimate the bandwidth and congestion window dynamically. The proposed Mobile Bandwidth Cloud Estimator (MBCE) algorithm helps to improve the bandwidth utilization based on the flow by considering the data size and Round-Trip Time. Similarly, the Cloud Estimation Congestion Window (CECW) algorithm aims to reduce the network congestion in the cloud by setting the congestion window dynamically. These two algorithms are implemented and tested in both the private cloud (Open Nebula) and the public cloud (Amazon Web Service). The result shows that the proposed MBCE utilizes 46% of actual bandwidth with smartphones in the cloud environment and improves the goodput by 27% in the private cloud and 24% in the public cloud. Moreover, the CECW algorithm decreases the Packet Loss Rate (PLR) by 0.344% in private cloud and 0.266% in public cloud environments when they are compared with other TCP variants.</p>