Balanced Parallel Scheduling for Video Encoding with Adaptive GOP Structure

Based on the Joint Video Team (JVT) of the ITU-T Video Coding Experts Group VC EG and the IS O/IEC Moving Picture Experts Group MPEG, an RD optimal Macro Block mode decision scheme for Internet error channel streaming is introduced. The scheme employs the luminance Rate Distortion (RD) optimal mode decision scheme so as to take the effects of video encoding distortion and the channel error propagation to get higher error robustness for error transmission. Based on the Wireless Sensor Network, this paper analyzes the data distortion problem when transmitting H.264 coded video stream over error-prone channel. And the authors also have discussed a widely accepted technique that introduces more intra-coded information on macro block basis. Additionally, this paper introduces a simple loss and multiplication factor estimation method, the rate-distortion optimized assessing strategy over the whole situation.

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A Survey of Low-Energy Parallel Scheduling Algorithms

IEEE Transactions on Sustainable Computing ◽

10.1109/tsusc.2021.3057983 ◽

2021 ◽

pp. 1-1

Author(s):

Guoqi Xie ◽

Xiongren Xiao ◽

Hao Peng ◽

Renfa Li ◽

Keqin Li

Keyword(s):

Scheduling Algorithms ◽

Low Energy ◽

Parallel Scheduling

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Decoding-workload-aware video encoding

Proceedings of the 18th International Workshop on Network and Operating Systems Support for Digital Audio and Video - NOSSDAV '08 ◽

10.1145/1496046.1496057 ◽

2008 ◽

Author(s):

Yicheng Huang ◽

Guangming Hong ◽

Vu An Tran ◽

Ye Wang

Keyword(s):

Video Encoding

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Content Dependent Representation Selection Model for Systems Based on MPEG DASH

Electronics ◽

10.3390/electronics10151843 ◽

2021 ◽

Vol 10 (15) ◽

pp. 1843

Author(s):

Jelena Vlaović ◽

Snježana Rimac-Drlje ◽

Drago Žagar

Keyword(s):

Mathematical Model ◽

Spatial Information ◽

Relevant Literature ◽

Video Quality ◽

Similarity Index ◽

Video Encoding ◽

Adaptation Algorithm ◽

Subjective Testing ◽

Proposed Model ◽

The Mathematical Model

A standard called MPEG Dynamic Adaptive Streaming over HTTP (MPEG DASH) ensures the interoperability between different streaming services and the highest possible video quality in changing network conditions. The solutions described in the available literature that focus on video segmentation are mostly proprietary, use a high amount of computational power, lack the methodology, model notation, information needed for reproduction, or do not consider the spatial and temporal activity of video sequences. This paper presents a new model for selecting optimal parameters and number of representations for video encoding and segmentation, based on a measure of the spatial and temporal activity of the video content. The model was developed for the H.264 encoder, using Structural Similarity Index Measure (SSIM) objective metrics as well as Spatial Information (SI) and Temporal Information (TI) as measures of video spatial and temporal activity. The methodology that we used to develop the mathematical model is also presented in detail so that it can be applied to adapt the mathematical model to another type of an encoder or a set of encoding parameters. The efficiency of the segmentation made by the proposed model was tested using the Basic Adaptation algorithm (BAA) and Segment Aware Rate Adaptation (SARA) algorithm as well as two different network scenarios. In comparison to the segmentation available in the relevant literature, the segmentation based on the proposed model obtains better SSIM values in 92% of cases and subjective testing showed that it achieves better results in 83.3% of cases.

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Passthrough+

Proceedings of the ACM on Computer Graphics and Interactive Techniques ◽

10.1145/3384540 ◽

2020 ◽

Vol 3 (1) ◽

pp. 1-17

Author(s):

Gaurav Chaurasia ◽

Arthur Nieuwoudt ◽

Alexandru-Eugen Ichim ◽

Richard Szeliski ◽

Alexander Sorkine-Hornung

Keyword(s):

Real Time ◽

Video Encoding ◽

View Synthesis ◽

Performance Constraints ◽

Trade Offs ◽

Stereoscopic View ◽

Target User ◽

Spatio Temporal ◽

And Performance ◽

3D Scene

We present an end-to-end system for real-time environment capture, 3D reconstruction, and stereoscopic view synthesis on a mobile VR headset. Our solution allows the user to use the cameras on their VR headset as their eyes to see and interact with the real world while still wearing their headset, a feature often referred to as Passthrough. The central challenge when building such a system is the choice and implementation of algorithms under the strict compute, power, and performance constraints imposed by the target user experience and mobile platform. A key contribution of this paper is a complete description of a corresponding system that performs temporally stable passthrough rendering at 72 Hz with only 200 mW power consumption on a mobile Snapdragon 835 platform. Our algorithmic contributions for enabling this performance include the computation of a coarse 3D scene proxy on the embedded video encoding hardware, followed by a depth densification and filtering step, and finally stereoscopic texturing and spatio-temporal up-sampling. We provide a detailed discussion and evaluation of the challenges we encountered, as well as algorithm and performance trade-offs in terms of compute and resulting passthrough quality.;AB@The described system is available to users as the Passthrough+ feature on Oculus Quest. We believe that by publishing the underlying system and methods, we provide valuable insights to the community on how to design and implement real-time environment sensing and rendering on heavily resource constrained hardware.

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Parallel Scheduling Algorithms Investigation of Support Strict Resource Reservation from Grid

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.519-520.108 ◽

2014 ◽

Vol 519-520 ◽

pp. 108-113 ◽

Cited By ~ 2

Author(s):

Jun Chen ◽

Bo Li ◽

Er Fei Wang

Keyword(s):

Parallel Computing ◽

Resource Utilization ◽

Scheduling Algorithm ◽

Scheduling Algorithms ◽

Resource Reservation ◽

Parallel Scheduling ◽

Scheduling Model ◽

Computing Grid ◽

Simulation Results ◽

Reservation Request

This paper studies resource reservation mechanisms in the strict parallel computing grid,and proposed to support the parallel strict resource reservation request scheduling model and algorithms, FCFS and EASY backfill analysis of two important parallel scheduling algorithm, given four parallel scheduling algorithms supporting resource reservation. Simulation results of four algorithms of resource utilization, job bounded slowdown factor and the success rate of Advanced Reservation (AR) jobs were studied. The results show that the EASY backfill + firstfit algorithm can ensure QoS of AR jobs while taking into account the performance of good non-AR jobs.

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