Modeling, Simulation and Analysis of Video Streaming Errors in Wireless Wideband Access Networks

Atayero, Aderemi A.; Sheluhin, Oleg I.; Ivanov, Yury A.

doi:10.1007/978-94-007-4786-9_2

Cited by 13 publications

(11 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The application BER value ensures that video quality (PSNR) is maintained at desired level. Note that it has been shown in [19] and [20] that BER below results in PSNR levels greater than 37 dB (corresponding to MOS value of 5 [19]) thereby ensuring high video quality for videos with different space-time characteristics. Hence, choosing value lesser than will ensure that PSNR of the received videos will be greater than 37 dB.…”

Section: A Download Rate and Mode Selection Problem Definitionmentioning

confidence: 98%

“…In addition to video quality, maintaining user experience also requires that does not exceed the network throughput in order to avoid video stalling. Hence bit rate selection to maximize battery level can be viewed as minimizing subject to bit rate, video quality and network throughput constraints as shown in (19). (19) Video quality is measured in terms of average MOS value, .…”

Section: A Maximization Of Battery Lifetime With Acceptable Qualitymentioning

confidence: 99%

“…Consequently, our approach needs to ensure that (1) the video download rate variation, including periods of idling, is done in a way that does not lead to buffer overflow or underflow (stalling of video playback), so that user experience is not affected; (2) the base station reconfiguration is done taking into account the wireless channel condition (estimated using Signal to Noise Ratio -SNR) so that a desired bit error [19], [20], and video quality) is satisfied; and (3) when additional video bit rate adaptation is done, a minimum video quality is satisfied in a way that increases the overall Video Experience Longevity.…”

Section: A Overall Approachmentioning

confidence: 99%

“…Since the original video resolution, bit rate, and frame rate are not changed by HTTP-PD, EERA or MoDS, the video quality is not affected. Further, by choosing a very low application BER, ( , [19], [20]) and carrying out mode selection so as to meet the desired application BER requirements ( in our experiments), no loss in PSNR and thereby video quality due to packet loss is ensured. Hence, the only user experience impairment in the case of video download techniques to be compared here is stalling.…”

Section: User Experience Modelmentioning

confidence: 99%

“…In other words, each snacking ratio value specified in user characteristics indicates how much of the corresponding video in the video sequence the user will watch. The value of the algorithm parameter, minimum buffer level, used to determine in (18) is also listed in Table V. Table V lists the channel conditions based on measurements of cellular network (high, low and variable) and the application BER requirement that ensures high quality (Section III-A, [19], [20]). Note the resolution of temporal variation in channel condition is assumed to be comparable to the simulation step.…”

Section: Simulation Frameworkmentioning

confidence: 99%

See 4 more Smart Citations

Battery Aware Video Delivery Techniques Using Rate Adaptation and Base Station Reconfiguration

Guruprasad

Dey

2015

IEEE Trans. Multimedia

View full text Add to dashboard Cite

With mobile video increasingly becoming an important driver of mobile device usage, the battery consumption of mobile devices will be dominated by video delivery and playback. In this paper, we develop battery efficient video download techniques that vary video download rate dynamically, including stopping video download at times, depending on mobile device buffer levels and the channel conditions experienced, to maximize battery life while ensuring no degradation in user experience. The proposed dynamic download rate adaptation techniques enable the base station to adapt the MIMO transceiver configurations to reduce battery load required by MIMO components on the mobile device. In order to further enhance battery life, we propose to utilize video bit rate adaptation, in addition to download rate adaptation and MIMO reconfiguration. The proposed battery aware bit rate adaptation techniques take into account the mobile device battery and buffer levels, and network load and channel conditions experienced, to maximize battery lifetime (hence video viewing time) while ensuring desired level of video experience (measured in terms of video quality and stalls experienced). We propose a new metric termed "video experience longevity (VEL)" which quantifies theperformance of the proposed bit rate adaptation techniques in terms of video viewing time and video experience. Extensive experiments conducted under variable channel conditions and network load demonstrate that the proposed battery aware video delivery techniques can significantly outperform other video delivery techniques in terms of battery lifetime and VEL metric (for bit rate adaptation techniques) while ensuring desired level of video experience.

show abstract

Section: A Download Rate and Mode Selection Problem Definitionmentioning

confidence: 98%

Section: A Maximization Of Battery Lifetime With Acceptable Qualitymentioning

confidence: 99%

Section: A Overall Approachmentioning

confidence: 99%

Section: User Experience Modelmentioning

confidence: 99%

Section: Simulation Frameworkmentioning

confidence: 99%

See 3 more Smart Citations

Battery Aware Video Delivery Techniques Using Rate Adaptation and Base Station Reconfiguration

Guruprasad

Dey

2015

IEEE Trans. Multimedia

View full text Add to dashboard Cite

show abstract

Analysis of Various Parameters for Link Adaptation in Wireless Transmission

Purandare

Kshirsagar

Koli³

2016

Advances in Intelligent Systems and Computing

View full text Add to dashboard Cite

Intellectual analysis and estimation of gross greenhouse gas emissions

Gorodnichev

Trofimenko

Potapchenko

et al. 2019

IOP Conf. Ser.: Earth Environ. Sci.

View full text Add to dashboard Cite

Currently, the system of accounting and monitoring of greenhouse gas emissions is being formed in the Russian Federation. It should be noted that within the framework of the system being formed, the transport sector is considered as the main contributor that generates large amounts of greenhouse gas emissions in cities and on busy federal highways. At the same time, it is proposed to take into account emissions directly when burning fuel only by road, city electric, rail, water and air transport. The article discusses methods for estimating gross emissions from road facilities using data mining methods aimed at verifying the results obtained. The article also presents the calculation of greenhouse gas emissions for road facilities in the pilot region with a description of the verification algorithm for the results obtained. The results of testing the methods for determining greenhouse gas emissions by road facilities showed that this calculation method can be used in estimating greenhouse gas emissions at road facilities, however, reliable baseline data for calculating gross greenhouse gas emissions can only be obtained by analyzing the activities of economic entities in transport and in the road sector. It should be borne in mind that business entities are not obliged to provide information constituting commercial secrets from their point of view. Therefore, the results obtained are of an estimated nature and relate only to those objects, data on which could be obtained from official statistics and free sources, while the actual amount of greenhouse gas emissions from road facilities in the pilot region during the period under review may be significantly higher.

show abstract

Modeling, Simulation and Analysis of Video Streaming Errors in Wireless Wideband Access Networks

Cited by 13 publications

References 2 publications

Battery Aware Video Delivery Techniques Using Rate Adaptation and Base Station Reconfiguration

Battery Aware Video Delivery Techniques Using Rate Adaptation and Base Station Reconfiguration

Analysis of Various Parameters for Link Adaptation in Wireless Transmission

Intellectual analysis and estimation of gross greenhouse gas emissions

Contact Info

Product

Resources

About