Estimating Perceived Video Quality from Objective Parameters in Video over IP Services

In Video over IP services, perceived video quality heavily depends on parameters such as video coding and network Quality of Service. This paper proposes a model for the estimation of perceived video quality in video streaming and broadcasting services that combines the aforementioned parameters with other that depend mainly on the information contents of the video sequences. These fitting parameters are derived from the Spatial and Temporal Information contents of the sequences. This model does not require reference to the original video sequence so it can be used for online, real-time monitoring of perceived video quality in Video over IP services. Furthermore, this paper proposes a measurement workbench designed to acquire both training data for model fitting and test data for model validation. Preliminary results show good correlation between measured and predicted values

Perceived Video Quality Estimation from Spatial and Temporal Information Contents and Network Performance Parameters in IPTV

The paper proposes a model for estimation of perceived video quality in IPTV, taking as input both video coding and network Quality of Service parameters. It includes some fitting parameters that depend mainly on the information contents of the video sequences. A method to derive them from the Spatial and Temporal Information contents of the sequences is proposed. The model may be used for near real-time monitoring of IPTV video quality

Joint On-the-Fly Network Coding/Video Quality Adaptation for Real-Time Delivery

This paper introduces a redundancy adaptation algorithm for an on-the-fly erasure network coding scheme called Tetrys in the context of real-time video transmission. The algorithm exploits the relationship between the redundancy ratio used by Tetrys and the gain or loss in encoding bit rate from changing a video quality parameter called the Quantization Parameter (QP). Our evaluations show that with equal or less bandwidth occupation, the video protected by Tetrys with redundancy adaptation algorithm obtains a PSNR gain up to or more 4 dB compared to the video without Tetrys protection. We demonstrate that the Tetrys redundancy adaptation algorithm performs well with the variations of both loss pattern and delay induced by the networks. We also show that Tetrys with the redundancy adaptation algorithm outperforms FEC with and without redundancy adaptation

A framework for qualitative communications using big packet protocol

In the current Internet architecture, a packet is a minimal or fundamental unit upon which different actions such as classification, forwarding, or discarding are performed by the network nodes. When faced with constrained or poor network conditions, a packet is subjected to undesirable drops and re-transmissions, resulting in unpredictable delays and subsequent traffic overheads in the network. Alternately, we introduce qualitative communication services which allow partial, yet timely, delivery of a packet instead of dropping it entirely. These services allow breaking down packet payloads into smaller units (called chunks), enabling much finer granularity of bandwidth utilization. We propose Packet Wash as anew operation in forwarding nodes to support qualitative services. Upon packet error or network congestion, the forwarding node selectively removes some chunk(s) from the payload based on the relationship among the chunks or the individual signiicance level of each chunk. We also present a qualitative communication framework as well as a Packet Wash directive implemented in a newly evolved data plane technology, called Big Packet Protocol (BPP)

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A Framework for Qualitative Communications Using Big Packet Protocol

In the current Internet architecture, a packet is a minimal or fundamental unit upon which different actions such as classification,forwarding, or discarding are performed by the network nodes.When faced with constrained or poor network conditions, a packet is subjected to undesirable drops and re-transmissions, resulting in unpredictable delays and subsequent traffic overheads in the network. Alternately, we introduce qualitative communication services which allow partial, yet timely, delivery of a packet instead of dropping it entirely. These services allow breaking down packet payloads into smaller units (called chunks), enabling much finer granularity of bandwidth utilization. We propose Packet Wash as a new operation in forwarding nodes to support qualitative services. Upon packet error or network congestion, the forwarding node selectively removes some chunk(s)from the payload based on the relationship among the chunks or the individual significance level of each chunk. We also present a qualitative communication framework as well as a Packet Wash directive implemented in a newly evolved data plane technology,called Big Packet Protocol (BPP)Comment: Accepted in NEAT workshop, ACM SIGCOMM, August 2019, Beijing, Chin

On combining temporal scaling and quality scaling for streaming MPEG

Temporal Scaling and Quality Scaling are both widely-used techniques to reduce the bitrate of streaming video. How-ever, combinations and comparisons of Temporal and Qual-ity Scaling have not been systematically studied. This re-search extends previous work to provide a model for combin-ing Temporal and Quality Scaling, and uses an optimization algorithm to provide a systematic analysis of their combina-tion over a range of network conditions and video content. Analytic experiments show: 1) Quality Scaling typically per-forms better than Temporal Scaling, with performance dif-ferences correlated with the motion characteristics of the video. In fact, when the network capacity is moderate and the loss rate is low, Quality Scaling performs nearly as well as the optimal combination of Quality and Temporal Scal-ing; 2) when the network capacity is low and the packet loss rate is high, Quality Scaling alone is ineffective, but a combination of Quality and Temporal Scaling can provide reasonable video quality; 3) adjusting the amount of For-ward Error Correction (FEC) provides significantly better performance than video streaming without FEC or video streaming with a fixed amount of FEC. 1