(untitled) (International Journal of Engineering and Computer Science, 2017)
Video streaming is a household term now-a-days and it is widely gaining a lot of popularity among mobile users. A wide variety of mobile devices,such as smart phones and tablets, are equipped with multiple wireless network interfaces. A lot of videos are streamed over the Internet according to users preferences but the question is how to efficiently and cost-effectively improve video streaming quality. In order to maintain high video streaming quality while reducing the wireless service cost,various approaches such as improving band with using adaptive algorithms are devised. In it,the optimal video streaming process with WIFI is done using bandwidth estimation and manipulation.Existing systems consider the quality of service (QoS) requirements for video traffic, such as the start up latency, playback fluency, average playback quality, playback smoothness and wireless service cost. Existing systems based on different survey’s include various bandwidth estimation tools such as Spruce,Pathload,PathChirp etc.These bandwidth estimation tools are based upon scenarios of probe gap model and probe rate model.these tools help to determine the available bandwidth based on the transmission of packets between sender and receiver the streaming quality is deduced and then the video streaming quality is adjusted according to that bandwidth as per user’s choice. The rate adaptation decision is made at the client side. For each segment, the client can request the appropriate quality version based on its screen resolution, current available bandwidth, and buffer occupancy status. We can let the client request different parts of one segment over different links. The main contributions is based upon threefolds. First, formulate the video streaming process over multiple links as an MDP problem. To achieve smooth and high quality video streaming, we define several actions and reward functions for each state, thus calculating the estimated bandwidth. Second, to propose an algorithm to perform bandwidth manipulation, this will take several future steps into consideration to avoid playback interruption and achieve better smoothness and quality. Last, we implement a realistic test bed using an Android phone and Scalable Video Coding (SVC) encoded videos to evaluate the performance. [3]