Enhancing the Smoothness of Streaming Video for Mobile Users over Unreliable Networks
|Author(s):||Hussein Muzahim Aziz|
|Title:||Enhancing the Smoothness of Streaming Video for Mobile Users over Unreliable Networks|
|Series:||Blekinge Institute of Technology Licentiate Dissertion Series|
|Publisher:||Blekinge Institute of Technology|
|Organization:||Blekinge Institute of Technology|
|Department:||School of Computing (Sektionen för datavetenskap och kommunikation)
School of Computing S-371 79 Karlskrona
+46 455 38 50 00
|Abstract:||Real time video streaming over wireless network is an increasingly important and attractive service to the mobile users. Video streaming involves a large amount of data to be transmitted in real time, while wireless channel conditions may vary from time to time. It is hard to guarantee a reliable transmission over the wireless network, where the parameters specifying the transmissions are; bandwidth, packet loss, packet delays, and outage times. The quality of the video is affected negatively when network packets are lost, and the mobile users may notice some sudden stop during the video playing; the picture is momentarily frozen, followed by a jump from one scene to a totally different one.
The main objective of this thesis is to provide a smooth video playback in the mobile device over unreliable networks with a satisfactory video quality. Three different techniques are proposed to achieve this goal. The first technique will stream duplicate gray scale frames over multichannels, if there is lost frames in one channel it can be recovered from another channel. In the second technique, each video frame will be split into sub-frames. The splitted sub-frames will be streamed over multichannels. If there is a missing sub-frame during the transmission a reconstruction mechanism will be applied in the mobile device to recreate the missing sub-frames. In the third technique, we propose a time interleaving robust streaming (TIRS) technique to stream the video frames in different order. The benefit of that is to avoid the losses of a sequence of neighbouring frames. A missing frame from the streaming video will be reconstructed based on the surrounding frames.
The mean opinion score (MOS) metric is used to evaluate the video quality. The experienced quality of a video is subject to the personal opinion, which is the only goal to satisfy the average human watching the contents of the video.