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Regulating QoE for adaptive video streaming using BBF method

HTTP video streaming becomes a main contributor in the ever increasing Internet traffic. It is not an easy task for the network service provider to guarantee the best user's Quality of Experience (QoE) in diverse networks with different access technologies. This requires an adaptive method that dynamically adapts the video quality service over HTTP according to time varying network conditions. In this paper, a client-based rate adaptive method is proposed that dynamically selects the appropriate video quality according to network conditions and user's device properties. The proposed method considers three important Quality of Service (QoS) factors that regulate the user's QoE for video streaming over HTTP, which are: Bandwidth, Buffer, and dropped Frame rate (BBF). The network bandwidth significantly affects the video service, as it directly reduces the client buffering that may result in pausing or stalling during video streaming. The proposed BBF method efficiently deals with sudden drop of network bandwidth by using the new bandwidth metric, and reduces its impact on the buffer level of the end user. The buffer length plays a vital role to handle the dynamic change in bandwidth. The dropped frame rate (fps) is another influential factor that minimizes the user's QoE. The proposed BBF algorithm is evaluated with different buffer length, and it is compared to Adobe's OSMF adaptive method.