Efficient and fair adaptive streaming: algorithm, implementation and evaluation

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2017
Öge, Ahmet
HTTP Adaptive Streaming (HAS) is a popular video streaming method where the client downloads video segments over standard HTTP protocol. In HAS, the server stores the video segments that are encoded in different qualities which determine the video bit rates. To this end, the client first downloads a file which describes the video segments. Then, using a rate adaptation algorithm, the client decides on the most appropriate video bit rate for the next segment to download and sends an HTTP request for that segment. The rate adaptation algorithm utilizes measurements of the network bandwidth by dividing the previously downloaded segments’ sizes by their download times. HAS exploits that HTTP is an ubiquitous application layer protocol which can easily pass any network device, firewall and Network Address Translation. Video streaming performance is measured by the user’s perception that is quantified by Quality of Experience (QoE). Accordingly, video freezes must be avoided as they decrease QoE significantly. The client aims for downloading at the highest quality utilizing the available bandwidth as much as possible. However, if the requested bit rate is increased too much, delays and packet loss events drive the client to decrease the bit rate subsequently. Such frequent rate switches decrease the QoE. Furthermore, it is desired that fairness among the clients is preserved where the clients that stream over a common bottleneck link share the bandwidth fairly. In this thesis, we provide an Efficient and Fair Adaptive STreaming (EFAST) architecture to improve the performance of HAS according to the performance metrics that are defined above. In this architecture, clients rate adaptation is implemented by using a Fuzzy Logic Controller. The inputs of EFAST Fuzzy Logic Controller are the receiver buffer size and the estimated bandwidth. After fuzzy control steps, it selects a proper video bit rate of next segment. An analytical model of rate adaptation algorithm is defined to show that EFAST achieves the desired bit rate and buffer occupancy. We implement EFAST in both simulation environment and in real life network. We then perform experiments that evaluate the performance of EFAST in comprehensive network scenarios. Furthermore, we compare EFAST to other wellknown HAS rate adaptation algorithms. Our results show that EFAST has more fairly bandwidth allocation among clients who share bottleneck, low switch rate changes, and high bottleneck efficiency with no buffer depletion.  

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Citation Formats
A. Öge, “Efficient and fair adaptive streaming: algorithm, implementation and evaluation,” M.S. - Master of Science, Middle East Technical University, 2017.