Stalling Assessment for Wireless Online Video Streams via ISP Traffic Monitoring

Tang, Hui; Chen, Liang; Wang, Yue; Wang, Na; Li, Xia

doi:10.1109/wcnc.2017.7925616

Cited by 5 publications

(4 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In [8], the authors adopted an approach, in which they reconstructed the video playback by monitoring the network traffic flow extracted from the HTTP meta information from the video packets. The authors in [9] followed a similar approach and tried to reconstruct the video playback parameters by analyzing the TCP and IP headers of video packets instead of the HTTP headers.…”

Section: Wts 2018 1570426654mentioning

confidence: 99%

“…We just use the throughput values delivered to the user device to reconstruct the video playback buffer and analyze it to detect the stalls. While the authors in [8] and [9] have considered just one video quality while estimating the stalls, in our proposed work we are considering three different video qualities while estimating the stalls.…”

Section: Wts 2018 1570426654mentioning

confidence: 99%

See 1 more Smart Citation

User throughput-based quality of experience evaluation for in flight video streaming

Hiranandani

Sarkar

Mihovska

et al. 2018

2018 Wireless Telecommunications Symposium (WTS)

View full text Add to dashboard Cite

Abstract-Satisfaction of end users is one of the most important factors for every service provider. Given that a lot of factors along with the network conditions affect the user's experience, the network quality given by the Quality of Service (QoS) parameters alone cannot provide an accurate measure of the users Quality of Experience (QoE). Today, most of the airlines have started providing in-flight wi-fi services, which allow the passengers to use various Internet services while on-board the flight, such as send and receive e-mails, stream video from diverse online service providers, and so forth. Statistics show that more than 50% of the passengers use the provided wi-fi service to stream video, therefore, their perception of the video service will be determining for the service provider's performance. One easy way to evaluate the perceived video streaming (i.e. QoE) is by estimating the frequency of stalls. In our paper, we propose an evaluation method based on the user throughput values to determine the number of stalls the user may have experienced during an adaptive video streaming service.Our algorithm is not dependent on any user device property and requires only one input, namely, the throughput values delivered to the user device, which can be collected at either the router or if available, at the traffic shaper.

show abstract

Section: Wts 2018 1570426654mentioning

confidence: 99%

Section: Wts 2018 1570426654mentioning

confidence: 99%

User throughput-based quality of experience evaluation for in flight video streaming

Hiranandani

Sarkar

Mihovska

et al. 2018

2018 Wireless Telecommunications Symposium (WTS)

View full text Add to dashboard Cite

show abstract

“…Based on the arrival method, service time distributions and number of servers, the queuing models are able to optimize metrics such as server utilization and reducing delays in the waiting time. Queuing has been used in monitoring Service Level Agreements (SLAs) processes [9], manufacturing [10], patient monitoring, video streaming [11], airport arrivals and departures [12] among others. Queuing can also be adopted by the data condition monitor, at the point of data reception, in order to avoid dropping of packets on arrival.…”

Section: Introductionmentioning

confidence: 99%

“…From equation(11), the system is stable if > ̅̅̅ . That is, the denominator tends to zero when = ̅̅̅Mean waiting time of a report in the queueFrom, Equation13, average report waiting time before processing is given by;̅̅̅̅ = ̅̅̅̅̅(14)Mean Service time for the reports ̅ ̅ =…”

mentioning

confidence: 99%

Condition Monitoring for Wireless Sensor Network-Based Automatic Weather Stations

Nsabagwa

Otim

Akol

et al. 2018

EAI Endorsed Trans IoT

View full text Add to dashboard Cite

Wireless Sensor Network (WSN)-based Automatic Weather Stations (AWSs) perform automatic collection and transmission of weather data. These AWSs face challenges, which lower their performance. Hence, a need for regular monitoring to reduce down time. We propose condition monitoring, comprised of a data receiver, analyser, problem classifier and reporter and visualizer, to mine data relationships, identify possible causes of problems and perform reporting of AWS status. The data receiver uses an M/M/1/k queuing model. We use Successive Pairwise REcord Differences (SPREDs) algorithm to compare arrival rates and packet content so as to establish sensor, node and AWS level performance. We also perform a hybrid of Grubb outlier detection and correlations amongst related variables for data validation. Problems take on one of four states. One connection can receive data at a rate as low as 1ms, without loss while problem identification especially in high density network is improved

show abstract

A Cooperative Vehicles Selection Method Based on Privacy-Preserving Driving Routes Comparison for Urban Scenarios

Wen

Liu

2020

2020 IEEE 5th International Conference on Cloud Computing and Big Data Analytics (ICCCBDA)

View full text Add to dashboard Cite

Stalling Assessment for Wireless Online Video Streams via ISP Traffic Monitoring

Cited by 5 publications

References 11 publications

User throughput-based quality of experience evaluation for in flight video streaming

User throughput-based quality of experience evaluation for in flight video streaming

Condition Monitoring for Wireless Sensor Network-Based Automatic Weather Stations

A Cooperative Vehicles Selection Method Based on Privacy-Preserving Driving Routes Comparison for Urban Scenarios

Contact Info

Product

Resources

About