• ETRI Journal
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• v.43 no.3
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• pp.447-458
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• 2021

The quality of experience (QoE) of video streaming is degraded by playback interruptions, which can be mitigated by the playout buffers of end users. To analyze the impact of playout buffer dynamics on the QoE of wireless adaptive hypertext transfer protocol (HTTP) progressive video, we model the playout buffer as a G/D/1 queue with an arbitrary packet arrival rate and deterministic service time. Because all video packets within a block must be available in the playout buffer before that block is decoded, playback interruption can occur even when the playout buffer is non-empty. We analyze the queue length evolution of the playout buffer using diffusion approximation. Closed-form expressions for user-perceived video quality are derived in terms of the buffering delay, playback duration, and interruption probability for an infinite buffer size, the packet loss probability and re-buffering probability for a finite buffer size. Simulation results verify our theoretical analysis and reveal that the impact of playout buffer dynamics on QoE is content dependent, which can contribute to the design of QoE-driven wireless adaptive HTTP progressive video management.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.6
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• pp.341-349
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• 2014

Dynamic adaptive streaming over HTTP (DASH) is the most recent and promising technology to support high quality streaming services. In dynamic adaptive streaming over HTTP (DASH), a client consecutively estimates the available network bandwidth and decides the transmission rate for the forthcoming video chunks to be downloaded. In this paper, we propose a novel rate adaptation algorithm called quality of experience QoE-enhanced adaptation algorithm over DASH (QAAD), which preserves the minimum buffer length to avoid interruption and minimizes the video quality changes during the playback. We implemented a DASH test bed and conducted extensive experiments. Experimental results demonstrate that under fluctuating network conditions, QAAD provides seamless streaming with stabilized video quality while the previous buffer-aware algorithm (i.e., QDASH[9]) frequently changes the video quality and undergoes the interruption.

• Journal of KIISE
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• v.44 no.12
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• pp.1296-1306
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• 2017

Recently, as the number of Internet of Things users has increased, IETF (Internet Engineering Task Force) has released the CoAP (Constrained Application Protocol). So Internet of Things have been researched actively. However, existing studies are difficult to adapt to streaming service due to low transmission rate that result from buffer underflow. In other words, one block is transmitted one block to client's one request according to the internet environment of limited resources. The proposed scheme adaptively adjusts the rate of CON(Confirmable) message among all messages for predicting the exact network condition. Based on this, the number of blocks is determined by using buffer occupancy rate and content download rate. Therefore it improves the quality of user experience by mitigating playback interruption. Experimental results show that the proposed scheme solves the buffer underflow problem in Internet of Things streaming environment by controlling transmission rate according to the network condition.