A novel marking mechanism for packet video delivery over diff serv networks

•Télécharger en tant que PPT, PDF•

2 j'aime•483 vues

Alpen-Adria-Universität

A Novel Marking Mechanism for Packet Video Delivery over DiffServ Networks Haidong Wang, Guizhong Liu School of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an China

Introduction ,[object Object],[object Object]

Introduction ,[object Object],[object Object],[object Object]

Introduction ,[object Object]

Introduction ,[object Object],[object Object]

Introduction ,[object Object],[object Object],[object Object],[object Object],[object Object]

Introduction ,[object Object],[object Object],[object Object],[object Object]

Introduction ,[object Object],[object Object],[object Object]

Introduction ,[object Object],[object Object],[object Object]

The Priority Classification Scheme ,[object Object],[object Object]

PATRTCM ,[object Object],[object Object]

PATRTCM ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

PATRTCM ,[object Object],[object Object],[object Object],[object Object],[object Object]

PATRTCM ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

PATRTCM ,[object Object],P green =1 P green =[Tp(t) － S － th 1 ] ／ (th 2 － th 1 ) P green =0 P green =0 P yellow =0 P yellow =1 － P green P yellow =[Tp(t) － S － th 0 ] ／ (th 1 － th 0 ) P yellow =0 P red =0 P red =0 P red =1 － P yellow P red =1 Tp(t) － S >th 2 th 1 <Tp(t) － S ≤th 2 th 0 <Tp(t) － S ≤th 1 Tp(t) － S ≤th 0

PATRTCM ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Simulation ,[object Object]

Simulation ,[object Object],[object Object]

Simulation ,[object Object],[object Object],[object Object]

Simulation ,[object Object]

Simulation ,[object Object],[object Object]

Simulation ,[object Object]

Results ( Highway )

Results (Foreman)

Conclusion ,[object Object],[object Object]

Thanks ！

Contenu connexe

Tendances

Compressive Sensing Based Adaptive Channel Estimation for TDS-OFDM System usi...

Compressive Sensing Based Adaptive Channel Estimation for TDS-OFDM System usi...

Compressive Sensing Based Adaptive Channel Estimation for TDS-OFDM System usi...

This paper evaluates the performance of OFDM - BPSK & -QPSK based system with and without channel estimation over Nakagami-m fading channels. Nakagami-m variants are generated by decomposition of Nakagami random variable into orthogonal random variables with Gaussian distribution envelopes. Performance of OFDM system in Nakagami channel has been reported here. The results yield the optimum value of m based on BER and SNR. Using this optimum value of m, Channel estimation over flat fading has been reported here. It has been depicted clearly from simulated graphs that channel estimation has further reduced the BER. However, threshold value of m has played a vital role during channel estimation.

On Channel Estimation of OFDM-BPSK and -QPSK over Nakagami-m Fading Channels

On Channel Estimation of OFDM-BPSK and -QPSK over Nakagami-m Fading Channels

On Channel Estimation of OFDM-BPSK and -QPSK over Nakagami-m Fading Channels

An OFDM system is combined with multiple-input mult iple-output (MIMO) in order to increase the diversity gain and system capacity over the time va riant frequency-selective channels. However, a maj or drawback of MIMO-OFDM system is that the transmitte d signals on different antennas might exhibit high peak-to-average power ratio (PAPR).In this paper, w e present a PAPR analysis reduction of space-time- block-coded (STBC) MIMO-OFDM system for 4G wireless networks. Several techniques have been used to reduce the PAPR of the (STBC) MIMOOFDM system: clip ping and filtering, partial transmit sequence (PTS) and selected mapping (SLM). Simulation result s show that clipping and filtering provides a bette r PAPR reduction than the others methods and only SLM technique conserve the PAPR reduction in reception part of signal.

Analyses and performance of techniques papr reduction for stbc mimo ofdm syst...

Analyses and performance of techniques papr reduction for stbc mimo ofdm syst...

Analyses and performance of techniques papr reduction for stbc mimo ofdm syst...

In this paper, we analyzed a numerical evaluation of the performance of MIMO radio systems in the LTE network environment. Downlink physical layer of the OFDM-MIMO based radio interface is considered for system model and a theoretical analysis of the bit error rate of the two space-time codes (SFBC 2×1 and FSTD 4×2 codes are adopted by the LTE norm as a function of the signal to noise ratio. Analytical expressions are given for transmission over a Rayleigh channel without spatial correlation which is then compared with Monte-Carlo simulations. Further evaluated channel capacity and simulation results show throughput almost reaches to the capacity limit.

9517cnc05

OFDM is one of the multicarrier modulation technique used in various communication systems. The major problem one faces while implementing this system is the high peak to average power .For an efficient OFDM system this PAPR should be low. In this paper a hybrid PAPR (peak to average power ratio) reduction technique for the OFDM (orthogonal frequency division multiplexing) signal which combines a multiple symbol representations method with a signal clipping method is proposed. In multiple symbol representations alternative signaling points are used to represent one symbol and PAPR is further reduced with the clipping scheme. The performance of the hybrid scheme is compared with the partial transmit sequence which is one of the other PAPR reduction scheme. In partial transmit sequence the input data is divided in to disjoint blocks transformed in to time domain sequence and rotated by phase factors. Theoretical analysis and simulation results validate that the proposed scheme has the ability to provide large PAPR reduction, low bit error rate. Performance analysis is also done with the partial transmit sequence scheme.

Performance of Multiple symbol representation with clipping scheme for PAPR r...

Performance of Multiple symbol representation with clipping scheme for PAPR r...

Performance of Multiple symbol representation with clipping scheme for PAPR r...

5G

ali_jasim_ramadan

IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.

Peak to–average power ratio reduction of ofdm siganls

Peak to–average power ratio reduction of ofdm siganls

Peak to–average power ratio reduction of ofdm siganls

eSAT Publishing House

Chapter 6

mimo

International Journal of Engineering Research and Applications (IJERA) is a team of researchers not publication services or private publications running the journals for monetary benefits, we are association of scientists and academia who focus only on supporting authors who want to publish their work. The articles published in our journal can be accessed online, all the articles will be archived for real time access. Our journal system primarily aims to bring out the research talent and the works done by sciaentists, academia, engineers, practitioners, scholars, post graduate students of engineering and science. This journal aims to cover the scientific research in a broader sense and not publishing a niche area of research facilitating researchers from various verticals to publish their papers. It is also aimed to provide a platform for the researchers to publish in a shorter of time, enabling them to continue further All articles published are freely available to scientific researchers in the Government agencies,educators and the general public. We are taking serious efforts to promote our journal across the globe in various ways, we are sure that our journal will act as a scientific platform for all researchers to publish their works online.

Ay4101287291

Orthogonal Frequency Division Multiplexing with Offset Quadrature Amplitude Modulation (OFDM / OQAM) is a multicarrier modulation scheme that can be considered as an alternative to the conventional Orthogonal Frequency Division Multiplexing (OFDM) with Cyclic Prefix (CP) for transmission over multipath fading channels. In this paper, we investigate the combination of the OFDM/OQAM with Alamouti system with Time Reversal (TR) technique. TR can be viewed as a precoding scheme which can be combined with OFDM/OQAM and easily carried out in a Multiple Input Single Output (MISO) context such as Alamouti system. We present the simulation results of the performance of OFDM/OQAM system in SISO case compared with the conventional CP-OFDM system and the performance of the combination Alamouti OFDM / OQAM with TR compared to Alamouti CP-OFDM. The performance is derived by computing the Bit Error Rate (BER) as a function of the transmit signal-to-noise ratio (SNR).

Alamouti ofdm

Presentation

International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.

Jx3417921795

Chien-Cheng Lai_Research Project

Chien-Cheng Lai_Research Project

Chien-Cheng Lai_Research Project

Multiplexing and spreading

Multiplexing and spreading

Multiplexing and spreading

Iisrt zzzz shamili ch

Iisrt zzzz shamili ch

Iisrt zzzz shamili ch

The work consists of the design of the chain drive system and the fabrication of the two axis parabolic solar dish. It is a model study of the two axis parabolic dish which worked by the automatic circuit that was developed. Ready made parabolic solar dish is taken and fabricated. The circular iron ring provides the two axis motion of the dish. A compound chain drive system was developed for the smooth movement of the dish. An electromechanical system which tracks the sun on both axes and which is controlled via a programmable logic control (PLC) was designed and implemented. In this a theoretical study was done. A C program was made which gave the required result for the graphical representation of the recorded radiation. Programmable Logic Controls (PLC) was used instead of photo sensors, which are widely used for tracking the sun. The azimuthal angle of the sun from sunrise to sunset times was calculated for each day of the year at 23.59 Lat & 72.38Longitude in the Northern hemisphere, the location of the city Mehsana. According to this azimuth angle, the required analog signal was taken from the PLC analog module and sent to the power window motor, which controlled the position of the panel to ensure that the rays fall vertically on the panel. After the mechanical control of the system was started, the performance measurements of the solar panel were carried out. The values obtained from the measurements were compared and the necessary evaluations were conducted.

Design and Fabrication of a Two Axis Parabolic Solar Dish Collector

Design and Fabrication of a Two Axis Parabolic Solar Dish Collector

Design and Fabrication of a Two Axis Parabolic Solar Dish Collector

Channel Estimation In The STTC For OFDM Using MIMO With 4G System

Channel Estimation In The STTC For OFDM Using MIMO With 4G System

Channel Estimation In The STTC For OFDM Using MIMO With 4G System

Tendances (18)

Compressive Sensing Based Adaptive Channel Estimation for TDS-OFDM System usi...

Compressive Sensing Based Adaptive Channel Estimation for TDS-OFDM System usi...

Compressive Sensing Based Adaptive Channel Estimation for TDS-OFDM System usi...

On Channel Estimation of OFDM-BPSK and -QPSK over Nakagami-m Fading Channels

On Channel Estimation of OFDM-BPSK and -QPSK over Nakagami-m Fading Channels

On Channel Estimation of OFDM-BPSK and -QPSK over Nakagami-m Fading Channels

Analyses and performance of techniques papr reduction for stbc mimo ofdm syst...

Analyses and performance of techniques papr reduction for stbc mimo ofdm syst...

Analyses and performance of techniques papr reduction for stbc mimo ofdm syst...

9517cnc05

Performance of Multiple symbol representation with clipping scheme for PAPR r...

Performance of Multiple symbol representation with clipping scheme for PAPR r...

Performance of Multiple symbol representation with clipping scheme for PAPR r...

5G

Peak to–average power ratio reduction of ofdm siganls

Peak to–average power ratio reduction of ofdm siganls

Peak to–average power ratio reduction of ofdm siganls

Chapter 6

mimo

Ay4101287291

Alamouti ofdm

Presentation

Jx3417921795

Chien-Cheng Lai_Research Project

Chien-Cheng Lai_Research Project

Chien-Cheng Lai_Research Project

Multiplexing and spreading

Multiplexing and spreading

Multiplexing and spreading

Iisrt zzzz shamili ch

Iisrt zzzz shamili ch

Iisrt zzzz shamili ch

Design and Fabrication of a Two Axis Parabolic Solar Dish Collector

Design and Fabrication of a Two Axis Parabolic Solar Dish Collector

Design and Fabrication of a Two Axis Parabolic Solar Dish Collector

Channel Estimation In The STTC For OFDM Using MIMO With 4G System

Channel Estimation In The STTC For OFDM Using MIMO With 4G System

Channel Estimation In The STTC For OFDM Using MIMO With 4G System

En vedette

IX Jornada Nacional de Bibliotecarios Escolares

IX Jornada Nacional de Bibliotecarios Escolares

IX Jornada Nacional de Bibliotecarios Escolares

2008 em Imagens by EquipeQMS

2008 em Imagens by EquipeQMS

2008 em Imagens by EquipeQMS

escuela de golf

escuela de golf

escuela de golf

Fondo Sostegno all'Affitto 2007 - Regione Veneto.

Fondo Sostegno all'Affitto 2007 - Regione Veneto.

Fondo Sostegno all'Affitto 2007 - Regione Veneto.

Claudio Goatelli

INTERNET COMO FONTE DE iNFORMACIÓN

INTERNET COMO FONTE DE iNFORMACIÓN

INTERNET COMO FONTE DE iNFORMACIÓN

Healthcare Here There Everywhere

Healthcare Here There Everywhere

Healthcare Here There Everywhere

Jack, Mazy Review

Jack, Mazy Review

Jack, Mazy Review

actividades

M health summit presentation final

M health summit presentation final

M health summit presentation final

A preliminary implementation of a content–aware network node

A preliminary implementation of a content–aware network node

A preliminary implementation of a content–aware network node

Alpen-Adria-Universität

Crowdfunding in de Zorg - Novartis Patient Academy

Crowdfunding in de Zorg - Novartis Patient Academy

Crowdfunding in de Zorg - Novartis Patient Academy

Ronald Kleverlaan

Měření návštěvnosti Optimalizátoři.cz

Měření návštěvnosti Optimalizátoři.cz

Měření návštěvnosti Optimalizátoři.cz

Tue 14 jun ilias eu-us- 14-6-11

Tue 14 jun ilias eu-us- 14-6-11

Tue 14 jun ilias eu-us- 14-6-11

mHealth Symposium 2013 Tjalling van der Schors

mHealth Symposium 2013 Tjalling van der Schors

mHealth Symposium 2013 Tjalling van der Schors

Der treue Johannes

Der treue Johannes

Der treue Johannes

Die sieben Raben

Die sieben Raben

Die sieben Raben

En vedette (16)

IX Jornada Nacional de Bibliotecarios Escolares

IX Jornada Nacional de Bibliotecarios Escolares

IX Jornada Nacional de Bibliotecarios Escolares

2008 em Imagens by EquipeQMS

2008 em Imagens by EquipeQMS

2008 em Imagens by EquipeQMS

escuela de golf

escuela de golf

escuela de golf

Fondo Sostegno all'Affitto 2007 - Regione Veneto.

Fondo Sostegno all'Affitto 2007 - Regione Veneto.

Fondo Sostegno all'Affitto 2007 - Regione Veneto.

INTERNET COMO FONTE DE iNFORMACIÓN

INTERNET COMO FONTE DE iNFORMACIÓN

INTERNET COMO FONTE DE iNFORMACIÓN

Healthcare Here There Everywhere

Healthcare Here There Everywhere

Healthcare Here There Everywhere

Jack, Mazy Review

Jack, Mazy Review

Jack, Mazy Review

actividades

M health summit presentation final

M health summit presentation final

M health summit presentation final

A preliminary implementation of a content–aware network node

A preliminary implementation of a content–aware network node

A preliminary implementation of a content–aware network node

Crowdfunding in de Zorg - Novartis Patient Academy

Crowdfunding in de Zorg - Novartis Patient Academy

Crowdfunding in de Zorg - Novartis Patient Academy

Měření návštěvnosti Optimalizátoři.cz

Měření návštěvnosti Optimalizátoři.cz

Měření návštěvnosti Optimalizátoři.cz

Tue 14 jun ilias eu-us- 14-6-11

Tue 14 jun ilias eu-us- 14-6-11

Tue 14 jun ilias eu-us- 14-6-11

mHealth Symposium 2013 Tjalling van der Schors

mHealth Symposium 2013 Tjalling van der Schors

mHealth Symposium 2013 Tjalling van der Schors

Der treue Johannes

Der treue Johannes

Der treue Johannes

Die sieben Raben

Die sieben Raben

Die sieben Raben

Similaire à A novel marking mechanism for packet video delivery over diff serv networks

I am Bernard. I am a Computer Networking Assignment Expert at computernetworkassignmenthelp.com. I hold a Master's in Computer Science from, University of Leeds, UK. I have been helping students with their assignments for the past 12 years. I solve assignments related to Computer Networking. Visit computernetworkassignmenthelp.com or email support@computernetworkassignmenthelp.com. You can also call on +1 678 648 4277 for any assistance with Computer Networking Assignment.

Computer Networking Assignment Help

Computer Networking Assignment Help

Computer Networking Assignment Help

Computer Network Assignment Help

Improving the performance of the transmission control protocol (TCP) in wireless environment has been an active research area. Main reason behind performance degradation of TCP is not having ability to detect actual reason of packet losses in wireless environment. In this paper, we are providing a simulation results for TCP-P (TCP-Performance). TCP-P is intelligent protocol in wireless environment which is able to distinguish actual reasons for packet losses and applies an appropriate solution to packet loss. TCP-P deals with main three issues, Congestion in network, Disconnection in network and random packet losses. TCP-P consists of Congestion avoidance algorithm and Disconnection detection algorithm with some changes in TCP header part. If congestion is occurring in network then congestion avoidance algorithm is applied. In congestion avoidance algorithm, TCP-P calculates number of sending packets and receiving acknowledgements and accordingly set a sending buffer value, so that it can prevent system from happening congestion. In disconnection detection algorithm, TCP-P senses medium continuously to detect a happening disconnection in network. TCP-P modifies header of TCP packet so that loss packet can itself notify sender that it is lost.This paper describes the design of TCP-P, and presents results from experiments using the NS-2 network simulator. Results from simulations show that TCP-P is 4% more efficient than TCP-Tahoe, 5% more efficient than TCP-Vegas, 7% more efficient than TCP-Sack and equally efficient in performance as of TCP-Reno and TCP-New Reno. But we can say TCP-P is more efficient than TCP-Reno and TCP-New Reno since it is able to solve more issues of TCP in wireless environment.

Improving Performance of TCP in Wireless Environment using TCP-P

Improving Performance of TCP in Wireless Environment using TCP-P

Improving Performance of TCP in Wireless Environment using TCP-P

This paper proposes and analyzes a novel differential distributed beamforming strategy for decentralized two-way relay networks. In our strategy, the phases of the received signals at all relays are synchronized without requiring channel feedback or training symbols. Bit error rate (BER) expressions of the proposed strategy are provided for coherent and differential M-PSK modulation. Upper bounds, lower bounds, and simple approximations of the BER are also derived. Based on the theoretical and simulated BER performance, the proposed strategy offers a high system performance and low decoding complexity and delay without requiring channel state information at any transmitting or receiving antenna. Furthermore, the simple approximation of the BER upper bound shows that the proposed strategy enjoys the full diversity gain which is equal to the number of transmitting antennas.

Performance Analysis of Differential Beamforming in Decentralized Networks

Performance Analysis of Differential Beamforming in Decentralized Networks

Performance Analysis of Differential Beamforming in Decentralized Networks

In this paper, we propose a novel advanced multi-rate design for evolved Multimedia Multicast/Broadcast Service (eMBMS) in fourth generation (4G) Long-Term Evolution (LTE)/LTE-Advanced (LTE-A) networks. The proposed design provides: i) reliability, based on random network coded (RNC) transmission, and ii) efficiency, obtained by optimized rate allocation across multi-rate RNC streams. The paper provides an in-depth description of the system realization and demonstrates the feasibility of the proposed eMBMS design using both analytical and simulation results. The system performance is compared with popular multi-rate multicast approaches in a realistic simulated LTE/LTE-A environment.

Presentation of 'Reliable Rate-Optimized Video Multicasting Services over LTE...

Presentation of 'Reliable Rate-Optimized Video Multicasting Services over LTE...

Presentation of 'Reliable Rate-Optimized Video Multicasting Services over LTE...

Wireless communication is one of the mainly active areas of tools progress and has become an ever more essential and prominent part of everyday life. Simulation of wireless channels accurately is very important for the intend and performance evaluation of wireless communication systems and components. We evaluated the act of available transmission modes in LTE. However, performance analysis can be done straightforward using evaluation of LTE. The performance of transmission modes are evaluated by calculating probability of Bit Error Rate BER versus Signal Noise Ratio SNR under the frequently used three wireless channel models AWGN, Rayleigh and Rician . We will consider the data modulation and data rate to analyze performance that is BER vs. SNR. A comparative analysis of QPSK and 16QAM, 32 QAM and 64 QAM will also provide knowledge base which helps for application development in real world. Parvesh Kumar | Shalini Bhadola | Kirti Bhatia ""Evaluation of BER in LTE System using Various Modulation Techniques over different Modulation Schemes"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3 , April 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23315.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/23315/evaluation-of-ber-in-lte-system-using-various-modulation-techniques-over-different-modulation-schemes/parvesh-kumar

Evaluation of BER in LTE System using Various Modulation Techniques over diff...

Evaluation of BER in LTE System using Various Modulation Techniques over diff...

Evaluation of BER in LTE System using Various Modulation Techniques over diff...

I010125056

RTP.ppt

Wcdma physical layer

Wcdma physical layer

Wcdma physical layer

IPHEADER_IPV4_IPV6_4.pdf

IPHEADER_IPV4_IPV6_4.pdf

IPHEADER_IPV4_IPV6_4.pdf

AbhishekKumar66407

Assignment cn tl

Assignment cn tl

Assignment cn tl

wn_Chapter_6_MAC.pdf

wn_Chapter_6_MAC.pdf

wn_Chapter_6_MAC.pdf

Abstract We deemed the PAPR reduction problem for OFDM/OQAM system. The PAPR reduction is the serious problem for implementations of both OFDM and OFDM/OQAM systems due to their high PAPR. The OFDM/OQAM signal is generated by summing over M time-shifted OFDM/OQAM symbols, where the successive symbols are interdependent with each other. The AS (Alternative-Signal) method directly leads to the independent AS (AS-I) and joint AS (AS-J) algorithms. The AS-I algorithm reduces the PAPR symbol by symbol with low complexity and AS-J applies optimal joint PAPR reduction among M OFDM/OQAM symbols with much higher complexity. A sequential optimization procedure denoted AS-S have been proposed to balance the computation complexity and system performance in this paper. AS-S algorithm, which adopts a sequential optimization procedure over time with computational complexity linearly increasing with M. The Simulation results have been provided for performance comparison of AS-I, AS-J, and AS-S algorithms. Keywords—Peak-to-Average power ratio (PAPR), orthogonal frequency division multiplexing with offset quadrature amplitude modulation (OFDM/OQAM), Alternative-signal(AS),cyclic prefix(CP).

Papr reduction for ofdm oqam signals via alternative signal method

Papr reduction for ofdm oqam signals via alternative signal method

Papr reduction for ofdm oqam signals via alternative signal method

Ad Hoc Probe

Fundamentals of sdh

Fundamentals of sdh

Fundamentals of sdh

With the advent of OFDM for WLAN communications, as exemplified by IEEE 802.11a, it has become imperative to have efficient and reliable synchronization algorithms for OFDM WLAN receivers. The main challenges with synchronization deal with the frequency offset and delay spread introduced by the wireless channel. In this paper, research is done into OFDM timing synchronization and frequency synchronization techniques.

Joint Timing and Frequency Synchronization in OFDM

Joint Timing and Frequency Synchronization in OFDM

Joint Timing and Frequency Synchronization in OFDM

TCP Vs UDP

The turbo detection of turbo coded symbols over correlated Rayleigh flat fading channels generated according to Jakes’ model is considered in this paper. We propose a method to estimate the channel signal-to-noise ratio (SNR) and the maximum Doppler frequency. These statistics are required by the linear minimum mean squared error (LMMSE) channel estimator. To improve the system convergence, we redefine the channel reliability factor by taking into account the channel estimation error statistics. Simulation results for rate 1/3 turbo code and two different normalized fading rates show that the use of the new reliability factor greatly improves the performance. The improvement is more substantial when channel statistics are unknown.

Turbo Detection in Rayleigh flat fading channel with unknown statistics

Turbo Detection in Rayleigh flat fading channel with unknown statistics

Turbo Detection in Rayleigh flat fading channel with unknown statistics

Packet에 대해서 알아보자.pdf

Packet에 대해서 알아보자.pdf

Packet에 대해서 알아보자.pdf

Transport Layer in Computer Networks (TCP / UDP / SCTP)

Transport Layer in Computer Networks (TCP / UDP / SCTP)

Transport Layer in Computer Networks (TCP / UDP / SCTP)

Hamidreza Bolhasani

Realtimetapan

Similaire à A novel marking mechanism for packet video delivery over diff serv networks (20)

Computer Networking Assignment Help

Computer Networking Assignment Help

Computer Networking Assignment Help

Improving Performance of TCP in Wireless Environment using TCP-P

Improving Performance of TCP in Wireless Environment using TCP-P

Improving Performance of TCP in Wireless Environment using TCP-P

Performance Analysis of Differential Beamforming in Decentralized Networks

Performance Analysis of Differential Beamforming in Decentralized Networks

Performance Analysis of Differential Beamforming in Decentralized Networks

Presentation of 'Reliable Rate-Optimized Video Multicasting Services over LTE...

Presentation of 'Reliable Rate-Optimized Video Multicasting Services over LTE...

Presentation of 'Reliable Rate-Optimized Video Multicasting Services over LTE...

Evaluation of BER in LTE System using Various Modulation Techniques over diff...

Evaluation of BER in LTE System using Various Modulation Techniques over diff...

Evaluation of BER in LTE System using Various Modulation Techniques over diff...

I010125056

RTP.ppt

Wcdma physical layer

Wcdma physical layer

Wcdma physical layer

IPHEADER_IPV4_IPV6_4.pdf

IPHEADER_IPV4_IPV6_4.pdf

IPHEADER_IPV4_IPV6_4.pdf

Assignment cn tl

Assignment cn tl

Assignment cn tl

wn_Chapter_6_MAC.pdf

wn_Chapter_6_MAC.pdf

wn_Chapter_6_MAC.pdf

Papr reduction for ofdm oqam signals via alternative signal method

Papr reduction for ofdm oqam signals via alternative signal method

Papr reduction for ofdm oqam signals via alternative signal method

Ad Hoc Probe

Fundamentals of sdh

Fundamentals of sdh

Fundamentals of sdh

Joint Timing and Frequency Synchronization in OFDM

Joint Timing and Frequency Synchronization in OFDM

Joint Timing and Frequency Synchronization in OFDM

TCP Vs UDP

Turbo Detection in Rayleigh flat fading channel with unknown statistics

Turbo Detection in Rayleigh flat fading channel with unknown statistics

Turbo Detection in Rayleigh flat fading channel with unknown statistics

Packet에 대해서 알아보자.pdf

Packet에 대해서 알아보자.pdf

Packet에 대해서 알아보자.pdf

Transport Layer in Computer Networks (TCP / UDP / SCTP)

Transport Layer in Computer Networks (TCP / UDP / SCTP)

Transport Layer in Computer Networks (TCP / UDP / SCTP)

Realtimetapan

Plus de Alpen-Adria-Universität

Video streaming constitutes 65 % of global internet traffic, prompting an investigation into its energy consumption and CO2 emissions. Video encoding, a computationally intensive part of streaming, has moved to cloud computing for its scalability and flexibility. However, cloud data centers’ energy consumption, especially video encoding, poses environmental challenges. This paper presents VEED, a FAIR Video Encoding Energy and CO2 Emissions Dataset for Amazon Web Services (AWS) EC2 instances. Additionally, the dataset also contains the duration, CPU utilization, and cost of the encoding. To prepare this dataset, we introduce a model and conduct a benchmark to estimate the energy and CO2 emissions of different Amazon EC2 instances during the encoding of 500 video segments with various complexities and resolutions using Advanced Video Coding (AVC) and High-Efficiency Video Coding (HEVC). VEED and its analysis can provide valuable insights for video researchers and engineers to model energy consumption, manage energy resources, and distribute workloads, contributing to the sustainability of cloud-based video encoding and making them cost-effective. VEED is available at Github.

VEED: Video Encoding Energy and CO2 Emissions Dataset for AWS EC2 instances

VEED: Video Encoding Energy and CO2 Emissions Dataset for AWS EC2 instances

VEED: Video Encoding Energy and CO2 Emissions Dataset for AWS EC2 instances

Alpen-Adria-Universität

Addressing climate change requires a global decrease in greenhouse gas (GHG) emissions. In today’s digital landscape, video streaming significantly influences internet traffic, driven by the widespread use of mobile devices and the rising popularity of streaming platforms. This trend emphasizes the importance of evaluating energy consumption and the development of sustainable and eco-friendly video streaming solutions with a low Carbon Dioxide (CO2) footprint. We developed a specialized tool, released as an open-source library called GREEM , addressing this pressing concern. This tool measures video encoding and decoding energy consumption and facilitates benchmark tests. It monitors the computational impact on hardware resources and offers various analysis cases. GREEM is helpful for developers, researchers, service providers, and policy makers interested in minimizing the energy consumption of video encoding and streaming.

GREEM: An Open-Source Energy Measurement Tool for Video Processing

GREEM: An Open-Source Energy Measurement Tool for Video Processing

GREEM: An Open-Source Energy Measurement Tool for Video Processing

Alpen-Adria-Universität

In HTTP adaptive live streaming applications, video segments are encoded at a fixed set of bitrate-resolution pairs known as bitrate ladder. Live encoders use the fastest available encoding configuration, referred to as preset, to ensure the minimum possible latency in video encoding. However, an optimized preset and optimized number of CPU threads for each encoding instance may result in (i) increased quality and (ii) efficient CPU utilization while encoding. For low latency live encoders, the encoding speed is expected to be more than or equal to the video framerate. To this light, this paper introduces a Just Noticeable Difference (JND)-Aware Low latency Encoding Scheme (JALE), which uses random forest-based models to jointly determine the optimized encoder preset and thread count for each representation, based on video complexity features, the target encoding speed, the total number of available CPU threads, and the target encoder. Experimental results show that, on average, JALE yield a quality improvement of 1.32 dB PSNR and 5.38 VMAF points with the same bitrate, compared to the fastest preset encoding of the HTTP Live Streaming (HLS) bitrate ladder using x265 HEVC open-source encoder with eight CPU threads used for each representation. These enhancements are achieved while maintaining the desired encoding speed. Furthermore, on average, JALE results in an overall storage reduction of 72.70%, a reduction in the total number of CPU threads used by 63.83%, and a 37.87% reduction in the overall encoding time, considering a JND of six VMAF points.

Optimal Quality and Efficiency in Adaptive Live Streaming with JND-Aware Low ...

Optimal Quality and Efficiency in Adaptive Live Streaming with JND-Aware Low ...

Optimal Quality and Efficiency in Adaptive Live Streaming with JND-Aware Low ...

Alpen-Adria-Universität

In the context of rising environmental concerns, this paper introduces VEEP, an architecture designed to predict energy consumption and CO2 emissions in cloud-based video encoding. VEEP combines video analysis with machine learning (ML)-based energy prediction and real-time carbon intensity, enabling precise estimations of CPU energy usage and CO2 emissions during the encoding process. It is trained on the Video Complexity Dataset (VCD) and encoding results from various AWS EC2 instances. VEEP achieves high accuracy, indicated by an 𝑅2-score of 0.96, a mean absolute error (MAE) of 2.41 × 10−5, and a mean squared error (MSE) of 1.67 × 10−9. An important finding is the potential to reduce emissions by up to 375 times when comparing cloud instances and their locations. These results highlight the importance of considering environmental factors in cloud computing.

VEEP: Video Encoding Energy and CO₂ Emission Prediction

VEEP: Video Encoding Energy and CO₂ Emission Prediction

VEEP: Video Encoding Energy and CO₂ Emission Prediction

Alpen-Adria-Universität

In today’s dynamic streaming landscape, where viewers access content on various devices and en- counter fluctuating network conditions, optimizing video delivery for each unique scenario is imperative. Video content complexity analysis, content-adaptive video coding, and multi-encoding methods are fundamental for the success of adaptive video streaming, as they serve crucial roles in delivering high-quality video experiences to a diverse audience. Video content complexity analysis allows us to comprehend the video content’s intricacies, such as motion, texture, and detail, providing valuable insights to enhance encoding decisions. By understanding the content’s characteristics, we can effi- ciently allocate bandwidth and encoding resources, thereby improving compression efficiency without compromising quality. Content-adaptive video coding techniques built upon this analysis involve dy- namically adjusting encoding parameters based on the content complexity. This adaptability ensures that the video stream remains visually appealing and artifacts are minimized, even under challenging network conditions. Multi-encoding methods further bolster adaptive streaming by offering faster encoding of multiple representations of the same video at different bitrates. This versatility reduces computational overhead and enables efficient resource allocation on the server side. Collectively, these technologies empower adaptive video streaming to deliver optimal visual quality and uninter- rupted viewing experiences, catering to viewers’ diverse needs and preferences across a wide range of devices and network conditions. Embracing video content complexity analysis, content-adaptive video coding, and multi-encoding methods is essential to meet modern video streaming platforms’ evolving demands and create immersive experiences that captivate and engage audiences. In this light, this dissertation proposes contributions categorized into four classes:

Content-adaptive Video Coding for HTTP Adaptive Streaming

Content-adaptive Video Coding for HTTP Adaptive Streaming

Content-adaptive Video Coding for HTTP Adaptive Streaming

Alpen-Adria-Universität

Quality of Experience (QoE) and QoE models are of an increasing importance to networked systems. The traditional QoE modeling for video streaming applications builds a one-size-fits-all QoE model that underserves atypical viewers who perceive QoE differently. To address the problem of atypical viewers, this paper proposes iQoE (individualized QoE), a method that employs explicit, expressible, and actionable feedback from a viewer to construct a personalized QoE model for this viewer. The iterative iQoE design exercises active learning and combines a novel sampler with a modeler. The chief emphasis of our paper is on making iQoE sample-efficient and accurate. By leveraging the Microworkers crowdsourcing platform, we conduct studies with 120 subjects who provide 14,400 individual scores. According to the subjective studies, a session of about 22 minutes empowers a viewer to construct a personalized QoE model that, compared to the best of the 10 baseline models, delivers the average accuracy improvement of at least 42% for all viewers and at least 85% for the atypical viewers. The large-scale simulations based on a new technique of synthetic profiling expand the evaluation scope by exploring iQoE design choices, parameter sensitivity, and generalizability.

Empowerment of Atypical Viewers via Low-Effort Personalized Modeling of Video...

Empowerment of Atypical Viewers via Low-Effort Personalized Modeling of Video...

Empowerment of Atypical Viewers via Low-Effort Personalized Modeling of Video...

Alpen-Adria-Universität

Quality of Experience (QoE) and QoE models are of an increasing importance to networked systems. The traditional QoE modeling for video streaming applications builds a one-size-fits-all QoE model that underserves atypical viewers who perceive QoE differently. To address the problem of atypical viewers, this paper proposes iQoE (individualized QoE), a method that employs explicit, expressible, and actionable feedback from a viewer to construct a personalized QoE model for this viewer. The iterative iQoE design exercises active learning and combines a novel sampler with a modeler. The chief emphasis of our paper is on making iQoE sample-efficient and accurate. By leveraging the Microworkers crowdsourcing platform, we conduct studies with 120 subjects who provide 14,400 individual scores. According to the subjective studies, a session of about 22 minutes empowers a viewer to construct a personalized QoE model that, compared to the best of the 10 baseline models, delivers the average accuracy improvement of at least 42% for all viewers and at least 85% for the atypical viewers. The large-scale simulations based on a new technique of synthetic profiling expand the evaluation scope by exploring iQoE design choices, parameter sensitivity, and generalizability.

Empowerment of Atypical Viewers via Low-Effort Personalized Modeling of Vid...

Empowerment of Atypical Viewers via Low-Effort Personalized Modeling of Vid...

Empowerment of Atypical Viewers via Low-Effort Personalized Modeling of Vid...

Alpen-Adria-Universität

HTTP Adaptive Streaming (HAS) methods divide a video into smaller segments, encoded at multiple pre-defined bitrates to construct a bitrate ladder. Bitrate ladders are usually optimized per title over several dimensions, such as bitrate, resolution, and framerate. This paper adds a new dimension to the bitrate ladder by considering the energy consumption of the encoding process. Video encoders often have multiple pre-defined presets to balance the trade-off between encoding time, energy consumption, and compression efficiency. Faster presets disable certain coding tools defined by the codec to reduce the encoding time at the cost of reduced compression efficiency. Firstly, this paper evaluates the energy consumption and compression efficiency of different x265 presets for 500 video sequences. Secondly, optimized presets are selected for various representations in a bitrate ladder based on the results to guarantee a minimal drop in video quality while saving energy. Finally, a new per-title model, which optimizes the trade-off between compression efficiency and energy consumption, is proposed. The experimental results show that decreasing the VMAF score by 0.15 and 0.39 while choosing an optimized preset results in encoding energy savings of 70% and 83%, respectively.

Optimizing Video Streaming for Sustainability and Quality: The Role of Prese...

Optimizing Video Streaming for Sustainability and Quality: The Role of Prese...

Optimizing Video Streaming for Sustainability and Quality: The Role of Prese...

Alpen-Adria-Universität

With the emergence of multiple modern video codecs, streaming service providers are forced to encode, store, and transmit bitrate ladders of multiple codecs separately, consequently suffering from additional energy costs for encoding, storage, and transmission. To tackle this issue, we introduce an online energy-efficient Multi-Codec Bitrate ladder Estimation scheme (MCBE) for adaptive video streaming applications. In MCBE, quality representations within the bitrate ladder of new-generation codecs (e.g., HEVC, AV1) that lie below the predicted rate-distortion curve of the AVC codec are removed. Moreover, perceptual redundancy between representations of the bitrate ladders of the considered codecs is also minimized based on a Just Noticeable Difference (JND) threshold. Therefore, random forest-based models predict the VMAF of bitrate ladder representations of each codec. In a live streaming session where all clients support the decoding of AVC, HEVC, and AV1, MCBE achieves impressive results, reducing cumulative encoding energy by 56.45%, storage energy usage by 94.99%, and transmission energy usage by 77.61% (considering a JND of six VMAF points). These energy reductions are in comparison to a baseline bitrate ladder encoding based on current industry practice.

Energy-Efficient Multi-Codec Bitrate-Ladder Estimation for Adaptive Video Str...

Energy-Efficient Multi-Codec Bitrate-Ladder Estimation for Adaptive Video Str...

Energy-Efficient Multi-Codec Bitrate-Ladder Estimation for Adaptive Video Str...

Alpen-Adria-Universität

This paper presents UtilML, a novel approach for tackling resource utilization prediction challenges in the computing continuum. UtilML leverages Long-Short-Term Memory (LSTM) neural networks, a machine learning technique, to forecast resource utilization accurately. The effectiveness of UtilML is demonstrated through its evaluation of data extracted from a real GPU cluster in a computing continuum infrastructure comprising more than 1800 computing devices. To assess the performance of UtilML, we compared it with two related approaches that utilize a Baseline-LSTM model. Furthermore, we analyzed the LSTM results against User-Predicted values provided by GPU cluster owners for task deployment with estimated allocation values. The results indicate that UtilML outperformed user predictions by 2% to 27% for CPU utilization prediction. For memory prediction, UtilML variants excelled, showing improvements of 17% to 20% compared to user predictions.

Machine Learning Based Resource Utilization Prediction in the Computing Conti...

Machine Learning Based Resource Utilization Prediction in the Computing Conti...

Machine Learning Based Resource Utilization Prediction in the Computing Conti...

Alpen-Adria-Universität

The exponential growth of computer game streaming has led to the development of Quality of Experience (QoE) metrics to evaluate user satisfaction and enjoyment during online gameplay and live streaming. Adaptive Bitrate (ABR) streaming is a recent technology that has been suggested to improve QoE. This method enhances the streaming experience, upholds visual quality, minimizes stall events, and boosts player retention. It achieves this by estimating network bottlenecks and selecting appropriate versions of the content that best match the available bandwidth rather than adjusting encoding parameters. To investigate the correlation between quality switching and stall events, a subjective test was conducted separately and comparatively with 71 participants. For more detailed and in-depth research, video games were analyzed with the Video Complexity Analyzer (VCA) tool and divided into three categories of different genres, camera view, and temporal complexity heatmap from the two sets of normal and action scenes. This study seeks to shed light on three unresolved issues pertinent to QoE in game streaming: (i) the user preferences towards quality switching and stall events across varied scenes and games, (ii) the user inclinations towards either a single, prolonged stall event or multiple, shorter stall events, and (iii) the impact of conspicuous quality switching on the user’s QoE. Results from the study provided valuable insights, both qualitatively and quantitatively. The study found a marked preference among users for quality switching over stall events across all types of game streaming, irrespective of the scene’s intensity. Furthermore, it was observed that multiple short-stall events were generally favored over a single long-stall event in streaming first-person shooting games. Interestingly, approximately half of the participants remained oblivious to quality switching during their game viewing sessions, and among those who noticed a change in quality, the alteration did not significantly impact their perceived QoE.

Evaluation of Quality of Experience of ABR Schemes in Gaming Stream

Evaluation of Quality of Experience of ABR Schemes in Gaming Stream

Evaluation of Quality of Experience of ABR Schemes in Gaming Stream

Alpen-Adria-Universität

Multimedia applications, mainly video streaming services, are currently the dominant source of network load worldwide. In recent Video-on-Demand (VoD) and live video streaming services, traditional streaming delivery techniques have been replaced by adaptive solutions based on the HTTP protocol. Current trends toward high-resolution (e.g., 8K) and/or low- latency VoD and live video streaming pose new challenges to end-to-end (E2E) bandwidth demand and have stringent delay requirements. To do this, video providers typically rely on Content Delivery Networks (CDNs) to ensure that they provide scalable video streaming services. To support future streaming scenarios involving millions of users, it is necessary to increase the CDNs’ efficiency. It is widely agreed that these requirements may be satisfied by adopting emerging networking techniques to present Network-Assisted Video Streaming (NAVS) methods. Motivated by this, this thesis goes one step beyond traditional pure client- based HAS algorithms by incorporating (an) in-network component(s) with a broader view of the network to present completely transparent NAVS solutions for HAS clients.

Network-Assisted Delivery of Adaptive Video Streaming Services through CDN, S...

Network-Assisted Delivery of Adaptive Video Streaming Services through CDN, S...

Network-Assisted Delivery of Adaptive Video Streaming Services through CDN, S...

Alpen-Adria-Universität

Over the last recent years, video streaming traffic has become the dominating service over mobile networks. The two main reasons for the growth of video streaming traffic are the improved capabilities of mobile devices and the emergence of HTTP Adaptive Streaming (HAS). Hence, there is a demand for new technologies to cope with the increasing traffic load while improving clients’ Quality of Experience (QoE). The network plays a crucial role in the video streaming process. One of the key technologies on the network side is Multi-access Edge Computing (MEC), which has several key characteristics: computing power, storage, proximity to the clients and access to network and player metrics. Thus, it is possible to deploy mechanisms at the MEC node that assist video streaming. This thesis investigates how MEC capabilities can be leveraged to support video streaming delivery, specifically to improve the QoE, reduce latency or increase storage and bandwidth savings.

Multi-access Edge Computing for Adaptive Video Streaming

Multi-access Edge Computing for Adaptive Video Streaming

Multi-access Edge Computing for Adaptive Video Streaming

Alpen-Adria-Universität

In the last decades, video streaming has been developing significantly. Among current technologies, HTTP Adaptive Streaming (HAS) is considered the de-facto approach in multimedia transmission over the internet. In HAS, the video is split into temporal segments with the same duration (e.g., 4s), each of which is then encoded into different quality versions and stored at servers. The end user sends requests to the server to retrieve segments with specific quality versions determined by an Adaptive Bitrate (ABR) algorithm for the purpose of adapting the throughput fluctuation. Though the majority of HAS-based media services function well even under throughput restrictions and variations, there are still significant challenges for multimedia systems, especially the tradeoff among the increasing content complexity, various time-related requirements, and Quality of Experience (QoE). Content complexity encompasses the increased demands for data, such as high-resolution videos and high frame rates, as well as novel content formats, such as virtual reality (VR) and augmented reality (AR). Time-related requirements include – but are not limited to – start-up delay and end-to-end latency. QoE can be defined as the level of satisfaction or frustration experienced by the user of an application or service. Optimizing for one aspect usually negatively impacts at least one of the other two aspects. This thesis tackles critical open research questions in the context of HAS that significantly impact the QoE at the client side.

Policy-Driven Dynamic HTTP Adaptive Streaming Player Environment

Policy-Driven Dynamic HTTP Adaptive Streaming Player Environment

Policy-Driven Dynamic HTTP Adaptive Streaming Player Environment

Alpen-Adria-Universität

The considerable surge in energy consumption within data centers can be attributed to the exponential rise in demand for complex computing workflows and storage resources. Video streaming applications are both compute and storage-intensive and account for the majority of today’s internet services. In this work, we designed a video encoding application consisting of codec, bitrate, and resolution set for encoding a video segment. Then, we propose VE-Match, a matching-based method to schedule video encoding applications on both Cloud and Edge resources to optimize costs and energy consumption. Evaluation results on a real computing testbed federated between Amazon Web Services (AWS) EC2 Cloud instances and the Alpen-Adria University (AAU) Edge server reveal that VE-Match achieves lower costs by 17%-78% in the cost-optimized scenarios compared to the energy-optimized and tradeoff between cost and energy. Moreover, VE-Match improves the video encoding energy consumption by 38%-45% and gCO2 emission by up to 80 % in the energy-optimized scenarios compared to the cost-optimized and tradeoff between cost and energy.

VE-Match: Video Encoding Matching-based Model for Cloud and Edge Computing In...

VE-Match: Video Encoding Matching-based Model for Cloud and Edge Computing In...

VE-Match: Video Encoding Matching-based Model for Cloud and Edge Computing In...

Alpen-Adria-Universität

The rapid growth of video streaming usage is a significant source of energy consumption, driven by improved internet connections and service offerings, the quick development of video entertainment, the deployment of Ultra High-Definition, Virtual and Augmented Reality, as well as an increasing number of video surveillance and IoT applications. To address this challenge, it is essential to understand the various components involved in energy consumption during video streaming, ranging from video encoding to decoding and displaying the video on the end user’s screen. Then, it is critical to measure energy consumption for each component accurately and conduct an in-depth analysis to develop energy-efficient strategies that optimize video streaming [1, 2, 3]. These components are classified into three categories [4]: (i) data centers, which include encoding, packaging, and storage on cloud data centers; (ii) networks, which include core network and access networks; and (iii) end-user devices which involve decoding, players, hardware, etc. In addition to identifying the primary components of video streaming that affect energy consumption, it is important to conduct a comprehensive analysis of the entire video streaming. It is also essential to balance energy optimization and service quality to ensure that energyefficient strategies are implemented without sacrificing the quality of video streaming services. This talk aims to provide insights into the components of video streaming that contribute to energy consumption and highlight the challenges associated with measuring their energy usage. I will also introduce the tools that can be used for energy measurements for those components and the possible and associated strategies that lie within energy efficiency. By accurately measuring energy consumption, digital media companies can effectively monitor and control their energy usage, ultimately leading to cost savings and improved sustainability.

Energy Consumption in Video Streaming: Components, Measurements, and Strategies

Energy Consumption in Video Streaming: Components, Measurements, and Strategies

Energy Consumption in Video Streaming: Components, Measurements, and Strategies

Alpen-Adria-Universität

The rapid growth of video streaming usage is a significant source of energy consumption, driven by improved internet connections and service offerings, the quick development of video entertainment, the deployment of Ultra High-Definition, Virtual and Augmented Reality, as well as an increasing number of video surveillance and IoT applications. However, it is essential to note that these advancements come at the cost of energy consumption. To address this challenge, it is essential to understand the various components involved in energy consumption during video streaming, ranging from video encoding to decoding and displaying the video on the end user’s screen. Then, it is critical to accurately measure energy consumption for each component and conduct an in-depth analysis to develop energy-efficient strategies that optimize video streaming. I categorize these components into three categories: (i) data centers, (ii) networks, and (iii) end-user devices. In this talk, my objective is to provide insights into the components of video streaming that contribute to energy consumption and highlight the challenges associated with measuring their energy usage. I will also introduce the tools that can be used for energy measurements for those components and the possible and associated strategies that lie within energy efficiency. By accurately measuring energy consumption, digital media companies can effectively monitor and control their energy usage, ultimately leading to cost savings and improved sustainability.

Exploring the Energy Consumption of Video Streaming: Components, Challenges, ...

Exploring the Energy Consumption of Video Streaming: Components, Challenges, ...

Exploring the Energy Consumption of Video Streaming: Components, Challenges, ...

Alpen-Adria-Universität

Video is evolving into a crucial tool as daily lives are increasingly centered around visual communication. The demand for better video content is constantly rising, from entertainment to business meetings. The delivery of video content to users is of utmost significance. HTTP adaptive streaming, in which the video content adjusts to the changing network circumstances, has become the de-facto method for delivering internet video. As video technology continues to advance, it presents a number of challenges, one of which is the large amount of data required to describe a video accurately. To address this issue, it is necessary to have a powerful video encoding tool. Historically, these efforts have relied on hand-crafted tools and heuristics. However, with the recent advances in machine learning, there has been increasing exploration into using these techniques to enhance video coding performance. This thesis proposes eight contributions that enhance video coding performance for HTTP adaptive streaming using machine learning.

Video Coding Enhancements for HTTP Adaptive Streaming Using Machine Learning

Video Coding Enhancements for HTTP Adaptive Streaming Using Machine Learning

Video Coding Enhancements for HTTP Adaptive Streaming Using Machine Learning

Alpen-Adria-Universität

Nowadays, HTTP Adaptive Streaming (HAS) has become the de-facto standard for delivering video over the Internet. More users have started generating and delivering high-quality live streams (usually 4K resolution) through popular online streaming platforms, resulting in a rise in live streaming traffic. Typically, the video contents are generated by streamers and watched by many audiences, geographically distributed in various locations far away from the streamers. The resource limitation in the network (e.g., bandwidth) is a challenging issue for network and video providers to meet the users’ requested quality. This dissertation leverages edge computing capabilities and in-network intelligence to design, implement, and evaluate approaches to optimize Quality of Experience (QoE) and end-to-end (E2E) latency of live HAS. In addition, improving transcoding performance and optimizing the cost of running live HAS services and the network’s backhaul utilization are considered. Motivated by the mentioned issue, the dissertation proposes five contributions in two classes: optimizing resource utilization and light-weight transcoding.

Optimizing QoE and Latency of Live Video Streaming Using Edge Computing a...

Optimizing QoE and Latency of Live Video Streaming Using Edge Computing a...

Optimizing QoE and Latency of Live Video Streaming Using Edge Computing a...

Alpen-Adria-Universität

5G and 6G networks are expected to support various novel emerging adaptive video streaming services (e.g., live, VoD, immersive media, and online gaming) with versatile Quality of Experience (QoE) requirements such as high bitrate, low latency, and sufficient reliability. It is widely agreed that these requirements can be satisfied by adopting emerging networking paradigms like Software-Defined Networking (SDN), Network Function Virtualization (NFV), and edge computing. Previous studies have leveraged these paradigms to present network-assisted video streaming frameworks, but mostly in isolation without devising chains of Virtualized Network Functions (VNFs) that consider the QoE requirements of various types of Multimedia Services (MS). To bridge the aforementioned gaps, we first introduce a set of multimedia VNFs at the edge of an SDN-enabled network, form diverse Service Function Chains (SFCs) based on the QoE requirements of different MS services. We then propose SARENA, an SFC-enabled ArchitectuRe for adaptive VidEo StreamiNg Applications. Next, we formulate the problem as a central scheduling optimization model executed at the SDN controller. We also present a lightweight heuristic solution consisting of two phases that run on the SDN controller and edge servers to alleviate the time complexity of the optimization model in large-scale scenarios. Finally, we design a large-scale cloud-based testbed, including 250 HTTP Adaptive Streaming (HAS) players requesting two popular MS applications (i.e., live and VoD), conduct various experiments, and compare its effectiveness with baseline systems. Experimental results illustrate that SARENA outperforms baseline schemes in terms of users’ QoE by at least 39.6%, latency by 29.3%, and network utilization by 30% in both MS services.

SARENA: SFC-Enabled Architecture for Adaptive Video Streaming Applications

SARENA: SFC-Enabled Architecture for Adaptive Video Streaming Applications

SARENA: SFC-Enabled Architecture for Adaptive Video Streaming Applications

Alpen-Adria-Universität

Plus de Alpen-Adria-Universität (20)

VEED: Video Encoding Energy and CO2 Emissions Dataset for AWS EC2 instances

VEED: Video Encoding Energy and CO2 Emissions Dataset for AWS EC2 instances

VEED: Video Encoding Energy and CO2 Emissions Dataset for AWS EC2 instances

GREEM: An Open-Source Energy Measurement Tool for Video Processing

GREEM: An Open-Source Energy Measurement Tool for Video Processing

GREEM: An Open-Source Energy Measurement Tool for Video Processing

Optimal Quality and Efficiency in Adaptive Live Streaming with JND-Aware Low ...

Optimal Quality and Efficiency in Adaptive Live Streaming with JND-Aware Low ...

Optimal Quality and Efficiency in Adaptive Live Streaming with JND-Aware Low ...

VEEP: Video Encoding Energy and CO₂ Emission Prediction

VEEP: Video Encoding Energy and CO₂ Emission Prediction

VEEP: Video Encoding Energy and CO₂ Emission Prediction

Content-adaptive Video Coding for HTTP Adaptive Streaming

Content-adaptive Video Coding for HTTP Adaptive Streaming

Content-adaptive Video Coding for HTTP Adaptive Streaming

Empowerment of Atypical Viewers via Low-Effort Personalized Modeling of Video...

Empowerment of Atypical Viewers via Low-Effort Personalized Modeling of Video...

Empowerment of Atypical Viewers via Low-Effort Personalized Modeling of Video...

Empowerment of Atypical Viewers via Low-Effort Personalized Modeling of Vid...

Empowerment of Atypical Viewers via Low-Effort Personalized Modeling of Vid...

Empowerment of Atypical Viewers via Low-Effort Personalized Modeling of Vid...

Optimizing Video Streaming for Sustainability and Quality: The Role of Prese...

Optimizing Video Streaming for Sustainability and Quality: The Role of Prese...

Optimizing Video Streaming for Sustainability and Quality: The Role of Prese...

Energy-Efficient Multi-Codec Bitrate-Ladder Estimation for Adaptive Video Str...

Energy-Efficient Multi-Codec Bitrate-Ladder Estimation for Adaptive Video Str...

Energy-Efficient Multi-Codec Bitrate-Ladder Estimation for Adaptive Video Str...

Machine Learning Based Resource Utilization Prediction in the Computing Conti...

Machine Learning Based Resource Utilization Prediction in the Computing Conti...

Machine Learning Based Resource Utilization Prediction in the Computing Conti...

Evaluation of Quality of Experience of ABR Schemes in Gaming Stream

Evaluation of Quality of Experience of ABR Schemes in Gaming Stream

Evaluation of Quality of Experience of ABR Schemes in Gaming Stream

Network-Assisted Delivery of Adaptive Video Streaming Services through CDN, S...

Network-Assisted Delivery of Adaptive Video Streaming Services through CDN, S...

Network-Assisted Delivery of Adaptive Video Streaming Services through CDN, S...

Multi-access Edge Computing for Adaptive Video Streaming

Multi-access Edge Computing for Adaptive Video Streaming

Multi-access Edge Computing for Adaptive Video Streaming

Policy-Driven Dynamic HTTP Adaptive Streaming Player Environment

Policy-Driven Dynamic HTTP Adaptive Streaming Player Environment

Policy-Driven Dynamic HTTP Adaptive Streaming Player Environment

VE-Match: Video Encoding Matching-based Model for Cloud and Edge Computing In...

VE-Match: Video Encoding Matching-based Model for Cloud and Edge Computing In...

VE-Match: Video Encoding Matching-based Model for Cloud and Edge Computing In...

Energy Consumption in Video Streaming: Components, Measurements, and Strategies

Energy Consumption in Video Streaming: Components, Measurements, and Strategies

Energy Consumption in Video Streaming: Components, Measurements, and Strategies

Exploring the Energy Consumption of Video Streaming: Components, Challenges, ...

Exploring the Energy Consumption of Video Streaming: Components, Challenges, ...

Exploring the Energy Consumption of Video Streaming: Components, Challenges, ...

Video Coding Enhancements for HTTP Adaptive Streaming Using Machine Learning

Video Coding Enhancements for HTTP Adaptive Streaming Using Machine Learning

Video Coding Enhancements for HTTP Adaptive Streaming Using Machine Learning

Optimizing QoE and Latency of Live Video Streaming Using Edge Computing a...

Optimizing QoE and Latency of Live Video Streaming Using Edge Computing a...

Optimizing QoE and Latency of Live Video Streaming Using Edge Computing a...

SARENA: SFC-Enabled Architecture for Adaptive Video Streaming Applications

SARENA: SFC-Enabled Architecture for Adaptive Video Streaming Applications

SARENA: SFC-Enabled Architecture for Adaptive Video Streaming Applications

Dernier

[BuildWithAI] Introduction to Gemini.pdf

[BuildWithAI] Introduction to Gemini.pdf

[BuildWithAI] Introduction to Gemini.pdf

Join our latest Connector Corner webinar to discover how UiPath Integration Service revolutionizes API-centric automation in a 'Quote to Cash' process—and how that automation empowers businesses to accelerate revenue generation. A comprehensive demo will explore connecting systems, GenAI, and people, through powerful pre-built connectors designed to speed process cycle times. Speakers: James Dickson, Senior Software Engineer Charlie Greenberg, Host, Product Marketing Manager

Connector Corner: Accelerate revenue generation using UiPath API-centric busi...

Connector Corner: Accelerate revenue generation using UiPath API-centric busi...

Connector Corner: Accelerate revenue generation using UiPath API-centric busi...

Following the popularity of "Cloud Revolution: Exploring the New Wave of Serverless Spatial Data," we're thrilled to announce this much-anticipated encore webinar. In this sequel, we'll dive deeper into the Cloud-Native realm by uncovering practical applications and FME support for these new formats, including COGs, COPC, FlatGeoBuf, GeoParquet, STAC, and ZARR. Building on the foundation laid by industry leaders Michelle Roby of Radiant Earth and Chris Holmes of Planet in the first webinar, this second part offers an in-depth look at the real-world application and behind-the-scenes dynamics of these cutting-edge formats. We will spotlight specific use-cases and workflows, showcasing their efficiency and relevance in practical scenarios. Discover the vast possibilities each format holds, highlighted through detailed discussions and demonstrations. Our expert speakers will dissect the key aspects and provide critical takeaways for effective use, ensuring attendees leave with a thorough understanding of how to apply these formats in their own projects. Elevate your understanding of how FME supports these cutting-edge technologies, enhancing your ability to manage, share, and analyze spatial data. Whether you're building on knowledge from our initial session or are new to the serverless spatial data landscape, this webinar is your gateway to mastering cloud-native formats in your workflows.

Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME

Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME

Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME

How to Troubleshoot Apps for the Modern Connected Worker

How to Troubleshoot Apps for the Modern Connected Worker

How to Troubleshoot Apps for the Modern Connected Worker

DBX First Quarter 2024 Investor Presentation

DBX First Quarter 2024 Investor Presentation

DBX First Quarter 2024 Investor Presentation

Passkeys: Developing APIs to enable passwordless authentication Cody Salas, Sr Developer Advocate | Solutions Architect - Yubico Apidays New York 2024: The API Economy in the AI Era (April 30 & May 1, 2024) ------ Check out our conferences at https://www.apidays.global/ Do you want to sponsor or talk at one of our conferences? https://apidays.typeform.com/to/ILJeAaV8 Learn more on APIscene, the global media made by the community for the community: https://www.apiscene.io Explore the API ecosystem with the API Landscape: https://apilandscape.apiscene.io/

Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...

Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...

Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...

Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood

Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood

Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood

Juan lago vázquez

Effective data discovery is crucial for maintaining compliance and mitigating risks in today's rapidly evolving privacy landscape. However, traditional manual approaches often struggle to keep pace with the growing volume and complexity of data. Join us for an insightful webinar where industry leaders from TrustArc and Privya will share their expertise on leveraging AI-powered solutions to revolutionize data discovery. You'll learn how to: - Effortlessly maintain a comprehensive, up-to-date data inventory - Harness code scanning insights to gain complete visibility into data flows leveraging the advantages of code scanning over DB scanning - Simplify compliance by leveraging Privya's integration with TrustArc - Implement proven strategies to mitigate third-party risks Our panel of experts will discuss real-world case studies and share practical strategies for overcoming common data discovery challenges. They'll also explore the latest trends and innovations in AI-driven data management, and how these technologies can help organizations stay ahead of the curve in an ever-changing privacy landscape.

TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery

TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery

TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery

MS Copilot expands with MS Graph connectors

MS Copilot expands with MS Graph connectors

MS Copilot expands with MS Graph connectors

Nanddeep Nachan

MINDCTI Revenue Release Quarter One 2024

MINDCTI Revenue Release Quarter One 2024

MINDCTI Revenue Release Quarter One 2024

Corporate and higher education. Two industries that, in the past, have had a clear divide with very little crossover. The difference in goals, learning styles and objectives paved the way for differing learning technologies platforms to evolve. Now, those stark lines are blurring as both sides are discovering they have content that’s relevant to the other. Join Tammy Rutherford as she walks through the pros and cons of corporate and higher ed collaborating. And the challenges of these different technology platforms working together for a brighter future.

Corporate and higher education May webinar.pptx

Corporate and higher education May webinar.pptx

Corporate and higher education May webinar.pptx

Rustici Software

Dubai, often portrayed as a shimmering oasis in the desert, faces its own set of challenges, including the occasional threat of flooding. Despite its reputation for opulence and modernity, the emirate is not immune to the forces of nature. In recent years, Dubai has experienced sporadic but significant floods, testing the resilience of its infrastructure and communities. Among the critical lifelines in this bustling metropolis is the Dubai International Airport, a bustling hub that connects the city to the world. This article explores the intersection of Dubai flood events and the resilience demonstrated by the Dubai International Airport in the face of such challenges.

Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...

Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...

Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...

Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows. We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases. This video focuses on the deployment of external web forms using Jotform for Bonterra Impact Management. This solution can be customized to your organization’s needs and deployed to support the common use cases below: - Intake and consent - Assessments - Surveys - Applications - Program registration Interested in deploying web form automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.

Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...

Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...

Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...

Jeffrey Haguewood

EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER

EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER

EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER

Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...

Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...

Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...

Abhishek Deb(1), Mr Abdul Kalam(2) M. Des (UX) , School of Design, DIT University , Dehradun. This paper explores the future potential of AI-enabled smartphone processors, aiming to investigate the advancements, capabilities, and implications of integrating artificial intelligence (AI) into smartphone technology. The research study goals consist of evaluating the development of AI in mobile phone processors, analyzing the existing state as well as abilities of AI-enabled cpus determining future patterns as well as chances together with reviewing obstacles as well as factors to consider for more growth.

Exploring the Future Potential of AI-Enabled Smartphone Processors

Exploring the Future Potential of AI-Enabled Smartphone Processors

Exploring the Future Potential of AI-Enabled Smartphone Processors

ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke

ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke

ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke

Product Anonymous

Keynote 2: APIs in 2030: The Risk of Technological Sleepwalk Paolo Malinverno, Growth Advisor - The Business of Technology Apidays New York 2024: The API Economy in the AI Era (April 30 & May 1, 2024) ------ Check out our conferences at https://www.apidays.global/ Do you want to sponsor or talk at one of our conferences? https://apidays.typeform.com/to/ILJeAaV8 Learn more on APIscene, the global media made by the community for the community: https://www.apiscene.io Explore the API ecosystem with the API Landscape: https://apilandscape.apiscene.io/

Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...

Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...

Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...

Webinar Recording: https://www.panagenda.com/webinars/why-teams-call-analytics-is-critical-to-your-entire-business Nothing is as frustrating and noticeable as being in an important call and being unable to see or hear the other person. Not surprising then, that issues with Teams calls are among the most common problems users call their helpdesk for. Having in depth insight into everything relevant going on at the user’s device, local network, ISP and Microsoft itself during the call is crucial for good Microsoft Teams Call quality support. To ensure a quick and adequate solution and to ensure your users get the most out of their Microsoft 365. But did you know that ‘bad calls’ are also an excellent indicator of other problems arising? Precisely because it is so noticeable!? Like the canary in the mine, bad calls can be early indicators of problems. Problems that might otherwise not have been noticed for a while but can have a big impact on productivity and satisfaction. Join this session by Christoph Adler to learn how true Microsoft Teams call quality analytics helped other organizations troubleshoot bad calls and identify and fix problems that impacted Teams calls or the use of Microsoft365 in general. See what it can do to keep your users happy and productive! In this session we will cover - Why CQD data alone is not enough to troubleshoot call problems - The importance of attributing call problems to the right call participant - What call quality analytics can do to help you quickly find, fix-, and prevent problems - Why having retrospective detailed insights matters - Real life examples of how others have used Microsoft Teams call quality monitoring to problem shoot problems with their ISP, network, device health and more.

Why Teams call analytics are critical to your entire business

Why Teams call analytics are critical to your entire business

Why Teams call analytics are critical to your entire business

Strategies for Landing an Oracle DBA Job as a Fresher

Strategies for Landing an Oracle DBA Job as a Fresher

Strategies for Landing an Oracle DBA Job as a Fresher

Remote DBA Services

Dernier (20)

[BuildWithAI] Introduction to Gemini.pdf

[BuildWithAI] Introduction to Gemini.pdf

[BuildWithAI] Introduction to Gemini.pdf

Connector Corner: Accelerate revenue generation using UiPath API-centric busi...

Connector Corner: Accelerate revenue generation using UiPath API-centric busi...

Connector Corner: Accelerate revenue generation using UiPath API-centric busi...

Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME

Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME

Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME

How to Troubleshoot Apps for the Modern Connected Worker

How to Troubleshoot Apps for the Modern Connected Worker

How to Troubleshoot Apps for the Modern Connected Worker

DBX First Quarter 2024 Investor Presentation

DBX First Quarter 2024 Investor Presentation

DBX First Quarter 2024 Investor Presentation

Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...

Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...

Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...

Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood

Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood

Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood

TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery

TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery

TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery

MS Copilot expands with MS Graph connectors

MS Copilot expands with MS Graph connectors

MS Copilot expands with MS Graph connectors

MINDCTI Revenue Release Quarter One 2024

MINDCTI Revenue Release Quarter One 2024

MINDCTI Revenue Release Quarter One 2024

Corporate and higher education May webinar.pptx

Corporate and higher education May webinar.pptx

Corporate and higher education May webinar.pptx

Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...

Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...

Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...

Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...

Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...

Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...

EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER

EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER

EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER

Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...

Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...

Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...

Exploring the Future Potential of AI-Enabled Smartphone Processors

Exploring the Future Potential of AI-Enabled Smartphone Processors

Exploring the Future Potential of AI-Enabled Smartphone Processors

ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke

ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke

ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke

Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...

Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...

Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...

Why Teams call analytics are critical to your entire business

Why Teams call analytics are critical to your entire business

Why Teams call analytics are critical to your entire business

Strategies for Landing an Oracle DBA Job as a Fresher

Strategies for Landing an Oracle DBA Job as a Fresher

Strategies for Landing an Oracle DBA Job as a Fresher

A novel marking mechanism for packet video delivery over diff serv networks

1. A Novel Marking Mechanism for Packet Video Delivery over DiffServ Networks Haidong Wang, Guizhong Liu School of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an China

2.

3.

4.

5.

6.

7.

8.

9.

10.

11.

12.

13.

14.

15.

16.

17.

18.

19.

20.

21.

22.

23. Results ( Highway )

24. Results (Foreman)

25.