Improving network qos parameters for video streaming in mobile cloud

Abstract

he enormous growth of cloud technology and widespread use of newlinesmart phones in recent years has led to the development of many applications newlinefor video downloading and video streaming. The continuous streaming of newlinevideo from the cloud to mobile devices faces many challenges in Quality of newlineService (QoS) parameters, namely bandwidth utilization, goodput, packet loss newlinedue to congestion, and delay. Some of the mobile networks exhibit low newlinebandwidth and congestion problems, and hence, the quality of the video newlinecommunicated through such networks is diminishing. To resolve these newlineproblems, we propose new techniques for dynamic bandwidth estimation and newlinecongestion window adjustment, which enhance the performance of mobile newlinecloud networks. The proposed algorithms, namely Mobile Bandwidth Cloud newlineEstimator (MBCE) and Cloud Estimation Congestion Window (CECW), help newlineto improve bandwidth utilization and reduce network congestion. MBCE newlineutilizes the available mobile bandwidth in the cloud more efficiently, based on newlinethe flow by considering the data size and Round Trip Time (RTT). The newlineCECW sets the congestion window dynamically to minimize congestion in newlinethe cloud network. We have carried out the implementation in three levels. In newlinethe first level, we performed the performance in a simulator. The second level newlinewas evaluated in a private cloud (OpenNebula), and the third level is newlineimplemented in the public cloud (Amazon Web Services). The experiments newlineconducted proved that the proposed MBCE utilizes 46% of actual bandwidth newlinewith smart phones in the cloud environment. The proposed MBCE improves newlinethe goodput by 27% in the private cloud and 24% in the public cloud. newlineMoreover, the proposed algorithm CECW decreases the Packet Loss Rate newline(PLR) by 0.344% in private cloud and 0.266% in public cloud environments newlinecompared with other TCP variants. To handle the mobile network traffic, newlinedelay, and congestion, we propose a novel framework, namely, network newlinetraffic-aware dynamic bandwidth estimation and congestion avoidance in the newlinemobile cloud. In this proposed framewo