QUVE: QoE Maximizing Framework for Video-Streaming

Kimura, Toshikiro; Yokota, Masahiro; Matsumoto, Atsushi; Takeshita, Keizo; Kawano, Takeshi; Sato, Kazumichi; Yamamoto, Hiroshi; Hayashi, Takanori; Shiomoto, Kohei; Miyazaki, Kenichi

doi:10.1109/jstsp.2016.2632060

Cited by 13 publications

(8 citation statements)

References 23 publications

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“…According to [ 74 ] the sample size must include 5% of error, 95% of confidence and 50% of heterogeneity. Taking those aspects in mind, we considered 25 people (16 men and 9 women to reflect the fact that usually there are more men than women dedicated in guard profession).…”

Section: Experimental Results: Discussionmentioning

confidence: 99%

Low Cost Efficient Deliverying Video Surveillance Service to Moving Guard for Smart Home

Gualotuña

Macías

Suárez

et al. 2018

Sensors

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Low-cost video surveillance systems are attractive for Smart Home applications (especially in emerging economies). Those systems use the flexibility of the Internet of Things to operate the video camera only when an intrusion is detected. We are the only ones that focus on the design of protocols based on intelligent agents to communicate the video of an intrusion in real time to the guards by wireless or mobile networks. The goal is to communicate, in real time, the video to the guards who can be moving towards the smart home. However, this communication suffers from sporadic disruptions that difficults the control and drastically reduces user satisfaction and operativity of the system. In a novel way, we have designed a generic software architecture based on design patterns that can be adapted to any hardware in a simple way. The implanted hardware is of very low economic cost; the software frameworks are free. In the experimental tests we have shown that it is possible to communicate to the moving guard, intrusion notifications (by e-mail and by instant messaging), and the first video frames in less than 20 s. In addition, we automatically recovered the frames of video lost in the disruptions in a transparent way to the user, we supported vertical handover processes and we could save energy of the smartphone's battery. However, the most important thing was that the high satisfaction of the people who have used the system.

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Section: Experimental Results: Discussionmentioning

confidence: 99%

Low Cost Efficient Deliverying Video Surveillance Service to Moving Guard for Smart Home

Gualotuña

Macías

Suárez

et al. 2018

Sensors

View full text Add to dashboard Cite

show abstract

“…Se determinó el tamaño de la muestra en consonancia con [24] (5% de error, con un nivel de confianza del 95% y una heterogenidad del 50%), obteniendo un total de 25 personas. Para la escala de opinión se utilizó la norma International Telecommunication Union (ITU) P.800.…”

Section: Resultados Experimentales De La Mitigación De Interrupciounclassified

Mitigando Efectos Adversos de Interrupciones del Servicio de Video-vigilancia del Hogar en Clientes WiFi inalámbricos

Gualotuña

Macías

Suárez

et al. 2017

Proceedings XIII Jornadas De Ingenieria Telematica - JITEL2017

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Resumen-Actualmente los sistemas de videovigilancia en el Hogar se pueden combinar con sensores para formar un sistema de muy bajo coste y fácil manejo por parte del usuario final. Un componente importante en este sistema es el servidor de video streaming en tiempo real a clientes Web que usan Wireless Fidelity. El servidor se puede instalar en open hardware como el Raspberry Pi y se puede ayudar de sensores arduino para detectar alarmas de intrusión o condiciones domóticas adversas en el Hogar. Sin embargo, el Wireless Fidelity tiene conocidos problemas que provoca interrupciones esporádicas e impredecibles del servicio de video y de poca duración que disparan la pérdida de frames de video clave para observar el estado del Hogar en un momento dado, mientras el cliente se mueve (después de recibir una alarma). Mitigar los efectos adversos de estas interrupciones es una tarea complicada que hemos trabajado durante años. La novedad es que ahora construimos un sistema de open hardware embebida y de bajo coste (con utilidad práctica a los ciudadanos), y software libre íntegramente basado en servicios Web que es interoperable y basado en ontologías (para incluir decisiones sofisticadas, smart, de reconectar el servicio interrumpido). El elevado valor de parámetros de calidad de experiencia de usuario avalan los buenos resultados alcanzados.Palabras Clave-Video-vigilancia, WiFi, Streaming, patrón de diseño software, RapBerry Pi, arduino.

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“…Duanmu and others [17] constructed a video streaming database to study human responses to the effects of video compression, initial buffering, and playback interruption. To maximize video streaming QoE, an estimation framework based on re‐buffering states and content encoding conditions was proposed in [18]. A video QoE‐monitoring prototype platform considering bit rates and re‐buffering was presented in [19].…”

Section: Related Workmentioning

confidence: 99%

Impact of playout buffer dynamics on the QoE of wireless adaptive HTTP progressive video

Xie

Chen

et al. 2021

ETRI Journal

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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.

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QUVE: QoE Maximizing Framework for Video-Streaming

Cited by 13 publications

References 23 publications

Low Cost Efficient Deliverying Video Surveillance Service to Moving Guard for Smart Home

Low Cost Efficient Deliverying Video Surveillance Service to Moving Guard for Smart Home

Mitigando Efectos Adversos de Interrupciones del Servicio de Video-vigilancia del Hogar en Clientes WiFi inalámbricos

Impact of playout buffer dynamics on the QoE of wireless adaptive HTTP progressive video

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