Evaluation of QoS and QoE for H.264/SVC Video Transmission with DCF and EDCA

7/25/2019 Evaluation of QoS and QoE for H.264/SVC Video Transmission with DCF and EDCA

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International Journal of Applied Engineering Research

ISSN 0973-4562 Volume 9, Number 22 (2014) pp. 16109-16112

Research India Publications

http://www.ripublication.com

Evaluation of QoS and QoE for H.264/SVC VideoTransmission with DCF and EDCA

1John Petearson Anzola A and

2Andrs Camilo Jimnez A

1Professor Faculty of Engineering, Electronics Engineering

Fundacion Universitaria Los Libertadores, Bogota Colombia

Email:[email protected]

2Professor Faculty of Engineering, Electronics Engineering

Fundacion Universitaria Los Libertadores, Bogota Colombia

Email:[email protected]

Abstract

In this article, video traffic H.264/SVC and evaluation QoS metrics analyzed by Delay

and Throughput in relation to the number of jumps performed by the AODV protocol inan ideal environment (without traffic) and no Ideal with DCF and EDCA traffic.

Particularly QoE obtain advantages from the point of view of the user, by encoding,

transmitting and decoding video in a simulation environment as NS2, by evaluating the

video framework myEvalSVC illustrated. In this way we can analyze the impact of the

transmission and retrieval of video in uncontrolled environments, such as Ad Hoc

networks with QoS and without QoS.

Key Words: H264/SVC, QoS, QoE, DCF, EDCA

1.

INTRODUCTIONWith the increase of video streaming on demand and in real time, with the proliferation of

video services over the Internet and with the exponential growth of mobile devices capable

of processing multimedia content, the wireless video communication is become an attractive

market niche, which is receiving attention from industry and academy as applications of

wireless video transmission every day are easier to implement and integrate multiple devices

with Wi-Fi.

Applications in Wireless Local Area Networks (WLAN), support video

streaming technologies (VoIP, IPTV, etc.). Their study is attractive due to mobility and

portability that wireless ad hoc networks offer as an alternative to infrastructure


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16110 John Petearson Anzola A and Andrs Camilo Jimnez A

networks, since the delivery of real time video imposes strict requirements on time and

bandwidth, emerging many problems as a Quality of Service (QoS) means.

This article describes how the basic medium access mechanism Distributed

Coordination Function (DCF) and Enhanced Distributed Channel Access (EDCA),

H.264/SVC and scalability analysis of jumps that presents the protocol Ad hoc

On-Demand Distance Vector (AODV), in order to obtain a quantitative and qualitative

analysis of the behavior of the video in Ad hoc networks, through simulations with the

framework built into NS2 myEvalSVC.

The myEvalSVC [1] framework to estimate the quality of video transmissions

H.264/SVC in NS2, supported on three main processes: encoding, transmission and

decoding video. For analysis of the observations QoS time constraints presented

metrics Throughput Delay and used. As for Quality of Experience (QoE) is concerned,

the visual comparison of the transmitted video regarding the received video andquantification of Video Quality Metrics through the Peak Signal-to-Noise Ratio

(PSNR) is analyzed.

2.QOS IN AD HOC NETWORKThe transmission of video streaming usually has time constraints and QoS requirements

sensitive to unpredictable changes which may occur in the network. Traditional networks

deliver Best Effort traffic and can not guarantee resource reservation or priority traffic,

treating all packets with the same priority, as in the case of DCF in wireless networks.

2.1. Distributed Coordination Function - DCFDCF is a technique for media access control for the IEEE 802.11 standard for wireless local

area networks, which uses the CSMA / CA method with a random delay algorithm called

"Backoff". In this algorithm, when a node wishes to transmit must listen in the first instance

channel status. If the node finds that the channel is idle for a time interval DCF Interframe

Space (DIFS), the node can start transmitting packets. If the channel is busy during the DIFS

time interval, the node must defer packet transmission to find free channel [2].

Once the transmitter/source node finds the channel free, it must send a request to initiate

transmission Request To Send (RTS). Destination/target node receives the RTS request and

waits for a time interval Short Interframe Spaces (SIFS), until the channel is free. If the

channel is free, the target node must respond with a Clear To Send (CTS) or RxBusy, if you

are receiving data from other nodes in the network. Once the transmitter/source node receivesthe CTS packet, it must wait a SIFS time interval prior to transmitting the data to the

destination/target node. When the target node receives the data, wait a SIFS time interval and

proceeds to transmit the Acknowledgement (ACK) or not received anything transmitted

negative acknowledgment (NAK) to the transmitting node/source [3].

It is noteworthy that during this process, the transmitter/source node and

destination/target only must wait SIFS time intervals for their communication processes,

while neighboring nodes must wait for DIFS time and contend for the channel making

requests transmission.

If the channel is busy during the DIFS time interval, the nodes that want to initiate the

transmission will have to postpone it. If multiple nodes contend for the channel, detect that the


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Evaluation of QoS and QoE for H.264/SVC Video Transmission 16111

channel is busy performing a request repeatedly until a node finds that the channel is free and

as a result of the above process collisions occur. DCF, in order to avoid such collisions

specifies a random Backoff, forcing a node to defer its access to the channel for additional

time interval determined by the following expression [4]:

Backoff Tiempo = Random (0,CW) x Slot_Time (1)

where CW is contention window.

2.2. Enhanced distributed channel access - EDCAEDCA is an access mechanism providing QoS based on traffic prioritization. This

prioritization is obtained introducing four Access Categorie (AC), which, classify the

traffic associated with the priorities of the user traffic or the network. Similarly the

IEEE 802.1D [1] standard is defined. In Table 1 the relative priorities between 802.1Dand 802.11e access categories is summarized [5].

Tabla 1. Relacin entre Prioridad y Categora de Acceso.

Priority Priority

802.1D

Description 802.1D Access Categorie

802.11e

Description 802.11e

Less 1 Background AC_BK Best Effort

2 - AC_BK Best Effort

0 Best Effort AC_BE Best Effort

3 Excellent Effort AC_BE Test Video

4 Controlled Load AC_BI Video5 Video AC_BI Video

6 Voice , Video AC_BO Voice

Higher 7 Signaling Network AC_BO Voice

Each access category has its own transmit queue characterized by the parameters

of network traffic. The prioritization between different categories of access is obtained

by suitably configuring traffic parameters in each queue. A scheme operating system

access categories shown in Figure 1, the parameters of interest are:

Arbitrary Inter-Frame Space Number (AIFSN): It is the minimum time interval

since the physical medium is detected as empty or available until the transmission

begins [6].

timeslotACAIFSNSIFSACAIFS _][][ (2)

Contention Window (CW): Is a random number generated in the range to launch

the timeout mechanism (backoff).

Transmit Opportunity (TXOP): The maximum duration of a time interval in which

the QSTA (Station with QoS) can be transmitted after the transmission opportunity

limit has elapsed.


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Fig. 1: Working model of 802.11e MAC layer

At the time that the data packets arrive at the MAC Service Access Point (SAP),

the MAC layer handles 802.11e properly classify incoming traffic, sending them to the

appropriate queue of the MAC Service Data Unit (MSDU) layer. Each of these units of

the different queues AC (Access Category) competes internally by the TXOP.

The algorithm internal struggle calculates the backoff timeout independently for

each AC line, according AIFSN, CW parameters and a random number. The timeout

mechanism is similar to DCF and tail with the lowest backoff win in the internalcompetition.

The AC queue winner externally compete for access to the wireless medium. The

algorithm external strife no significant changes compared with DCF, DCF except that

the Backoff and timeouts are fixed, in contrast to 802.11e, which are variable and are

properly configured according to the corresponding AC queue.

Through proper setting of the parameters of the AC queue, traffic performance is

tight and can be achieved by prioritizing traffic. This requires a QoS Capable Access

Points (QAP) to maintain a common set of parameters in the queues and guarantee fair

access between the different stations that compose the QoS Enabled Basic Service Set

(QBSS) network. Similarly, in order to adjust the asymmetry between upstream

traffic/incoming qsta to the QAP and down/outgoing to QSTA QAP, a separate set ofEDCA parameters defined exclusively for the QAP [7]. Figure 2 compared the medium

access mechanism EDCA referring to DCF.


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Fig. 2: Comparison of model performance in DCF and EDCA

3. SCALABLE VIDEO CODING (SVC)

The H.264/MPEG-4 AVC standard provides a scalable extension called H.264/SVC

[5], considered the first standard that defines the multidimensional scalability.

H.264/SVC achieves a significant compression performance and reduce the complexity

of processing and acceptability in the applications or services, as perceived subjectively

the end user, presenting a high Quality of Experience (QoE) [8] .

The H.264/SVC schemes are known for the dissemination of video streaming services

in low resolution and multicast applications to suit different abilities depending on the

receptor and the ability to image retrieval in proportion to the variation of bandwidth

[9]. H.264/SVC reuses the main features of H.264/MPEG-4 Advanced Video Coding

and other techniques used to provide scalability extensions and improve coding gain.


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Fig. 3: Diagrammatic representation of SVC scalabilities

Overall SVC can provide three types of scalability: temporal, spatial and SNR

quality, allowing multiple video representations thus adapting to the speed and quality

levels for streaming video.

Fig. 4: H.264 SVC Stream


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In SVC, the bitstream is divided into a base layer and one or more enhancement

layers. The base layer is considered more important than the enhancement layers, as in

this layer needs less transmission bandwidth and the minimum acceptable contains

video information. Enhancement layers require more bandwidth for the definition and

enhancement of details that enhance its quality. Figure 3 is a schematic representation

of scalabilities SVC and Figure 4 shows the H.264/SVC Layered Structure.

Spatial scalability refers to the ability to represent the same video in different

resolutions and screen sizes, including: QCIF, CIF and 4CIF. In general, the spatially

encoded scalable video using images in the space used by the lower layers as a

prediction of the higher layers in order to further improve coding efficiency.

Temporal scalability refers to the possibility of representing the same video at

different temporal resolutions and frame rates, ie, the number of frames contained in the

first second of the video allow the video to be played at different frame rates. Usuallydone using temporary sample images from a lower layer as a top layer prediction.

Quality scalability, also called scalability of signal to noise ratio (SNR), refers to

the possibility of representing the same video at different levels of perceptual quality.

The SNR scalable encoding coefficients quantized Discrete Cosine Transform (DCT) at

different levels of accuracy by using different quantization parameters.

3. myEvalSVCmyEvalSVC is a framework for evaluating H.264/SVC built into NS2, based on

Scalable Video-streaming Evaluation Framework (SVEF) [10], which allows evaluating

network topologies, architectures and routing protocols realistically. myEvalSVCprocess starts by encoding YUV video format, in which you can set encoding

parameters (temporal, spatial, or combined SNR). Once selected encoding parameters,

we proceed to pass the video modules BitStreamExtractor which is developed by JSVM

and developped by FN Stamp SVEF, in order to generate a trace file NALU [11].

With the trace file NALU is necessary to create a compatible file in NS2, for this a

filter developed by myEvalSVC prepare_sendtrace.awk, which delivers a trace is used

completely compatible and integrated in the simulator. For reading and use of this

traceis necessary declare a myEvalSVC agent, which allows to design and evaluate the

performance of the SVC transmission topologies, protocols, and network architectures.

Within the simulator must be configured myEvalSVC_Sink their Agent, which is

used to receive packets SVC that record the time, the packet size, number of frame in atrace file output. With the information in this trace file can be extracted by creating

filters awk calculate different network metrics. At this point can be evaluated QoS and

performance of any scenario that video transport.

To evaluate QoE from the point of view of the user, myEvalSVC decode the video

that came on the receiver or target node, it is necessary to begin the process of decoding.

The decoding process starts by filtering the trace file using the filter

prepare_receivedtrace1.awk and prepare_receivedtrace2.exe, both developed by

myEvalSVC. The resulting file is processed by the SVEF module, which generates a

trace file that deletes NALU packets that arrived too late and could not be decoded.

After filtering the NALU trace output file is sent to BitStreamExtractor module, which


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generates a trace of H.264, which is then filtered by the JSVM decoder that generates a

file YUV video output. At this point QoE can be evaluated through the comparison of

input PSNR and output PSNR and by reconstructing the video [1].

Fig. 5: Framework myEvalSVC

4. PERFORMANCE METRICSInside the transmission of streaming video are the most important constraints related to

time and bandwidth, therefore, the Delay and Throughput is highlighted as measures

overall performance, which analyze the behavior of video within Ad Hoc networks. Themetric to be analyzed are:

4.1. Average end-to-end delayThe Average end-to-end delay [12] is defined as the time difference between the instant

when a packet is received by the destination node and the instant of time that has been

sent by a source node. Within the video transmission applications must comply with the

standard QoS and packet delay must be limited and decreased for high performance

transmission. The Average end-to-end delay has been calculated as shown in Equation

3:


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r

N

i

i

t

i

r

AVGN

HH

T

r

1 (3)

where, itH represents the transmission instant of package i,

i

rH represents reception

instant of package i, rN is the total number of packets received.

4.2. ThroughputThe Throughput [13] is defined as the number of bits successfully received on the target

node divided by the total transmission time in seconds, also interpreted as the ratio of

successfully Transmitted data per second, emphasizing that the minimum bandwidth

restrictions are required in a video stream to satisfy QoS requirements. The throughputis calculated as shown in Equation 4:

)(fRL

CLT

(4)

where, fRL

CL

is the payload transmission rate,Ris the Binary transmission rate

in bits/seconds and )(f is the packet success rate defined as the probability of

receiving a packet correctly. This probability is a function of the signal-to-noise ratio

)( .

5. SETTING THE SIMULATIONThis section describes the methodology used in the simulation and evaluation metrics

Delay and Throughput described considering a scenario described in Table 1. The

scenario considers the transmission of H.264/SVC between the pair of source/target

with UDP and TCP traffic backgraund between 16 nodes (8 nodes transmitting and

receiving nodes 8) to a uniform and constant velocity nodes. The main interest of this

paper is to analyze the metrics of delay and throughput in terms of hops (1-5 hops), as

displayed in Figure 6 between the pair of source/target nodes in ideal conditions (notraffic background) and in environments where all nodes have a DCF and EDAC

mechanism for providing access QoS.


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Table 1. configuration parameters of the simulation

Short Interframe Space (SIFS) 10us

Time slot 20us

DCF Interframe Space (DIFS) 50us

CWmin 32

CWmax 1024

Physical Header 192bits

MAC Header 224bits

ACK 112bits

Data rate 1Mbps

Basic rate 1Mbps

Sending rate of CBR flow 1 0.2MbpsSending rate of CBR flow 2 0.3Mbps

Play-out delay 5s

Size of the simulation area 1000m x 1000m

Antenna coverage 250m

Total of nodes 50

Protocol AODV

Constant speed (nodes) 6m/s

The test sequence used corresponds to video file "Foreman" [15] YUV CIF

(352X288) with 300 frames and encoded by JSVM where temporal scalability to the

results presented in this article is enable.


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Fig. 6: Scenarios Employees

6.SIMULATION RESULTS: EVALUATION OF QoE

Fig. 7: Video received DCF and EDCA

One of the main features of myEvalSVC lies video recovery in the target node,

appreciating the initial delay that causes the network. In case of packet loss

myEvalSVC replaces the lost image of the last image who arrived correct package.

The Peak Signal-to-Noise Ratio (PSNR) may be considered as a QoE metric,

since the quality of the received image is evaluated. In a video stream H.264/SVC base

layer is transmitted and sometimes finds that packet loss can be lost enhancement

layers. Although to the naked eye many of these losses are not significant, the PSNR

provides a quantitative measure of the quality of video that is being perceived. This

paper provides the results for a jump is shown by the high number of simulations.


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Fig. 8: PSNR original video with DCF and EDCA traffic for a traffic jumpBackground.

The routing protocol used for the assessment is Ad hoc On-Demand Distance

Vector (AODV), used by all mobile nodes in the proposed network, which offers the

following features [14]:

Rpida adaptation to changes in dynamic link Bajo processing and memory overhead

Baja use of network resources Determinacin route unicast destination

AODV uses destination sequence numbers to ensure lasos routing traffic,

preventing problems like counting to infinity associated with classical distance vector

protocols.

7. SIMULATION RESULTS: EVALUATION OF QoS

The following simulation results show the characterization of video traffic H.264/SVCin ad hoc networks for the scenario described in Figure 6, by analyzing the Delay vs. the

number of hops and throughput vs the number of hops, as observed in Figure 9 and 10.


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Fig. 9: Delay vs Jumps

Fig. 10: Throughput vs Jumps

The above results show a proportional increase between the number of hops and

delay for a constant speed of 6m/s, finding that 90% of the video is encoded for the same

scenarios or less than two jumps.

For scenarios equal to or greater than the three top video decoding than 10% and

therefore higher packet loss, which is reflected in the persepcion QoE is presented.

In the figure 10 shown throughput metrics and evaluation of network performance

at a constant speed and end to end delay is analyzed, noting that traffic packets to


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transmit video H.264SVC a DCF mechanism in his first two jumps delay is low and

adapts its throughput to Best Effort traffic because all packets in DCF are treated with

the same priority.

By contrast, when the video traffic is transmitted in a H.264SVC EDCA

mechanism allows prioritize packets Best Effort traffic and traffic with a lower priority

Background, giving precedence first to the voice traffic and secondly to traffic video.

Therefore, EDCA may reach rates of less than 10ms delay obtaining a bandwidth of

0.6Mbps and a jump two 0.26Mbps obtained jumps where video packet loss H.264SVC

less than 10% (with traffic Best Effort and Background) network ensure proper

decoding at the target node.

However, the ideal traffic (no Background and Best Effort traffic) in DCF is

comparable to the results obtained with EDCA traffic.

Figure 8 shows PSNR values for different access methods. The upper curverepresents the ideal values of PSNR NALU lossless (original video), the other two

curves correspond to the transmission of video using EDCA and DCF, noting that DCF

has less video Quality of EDCA, this interpretation traduciendoce QoE for user.

8. CONCLUSIONSIn this paper, QoS and QoE evaluated in providing video H.264SVC in WLANs through

the DCF and EDCA mechanisms, assessing the quality of streaming video, five primary

scenarios were simulated by highlighting the number of jumps performed by the AODV

protocol to deliver video to a target node. The results showed that reducing the

throughput depending on the number of hops decreases the available bandwidth whilemaintaining the video until the third and fourth jump with only EDCA mechanism,

except that the DCF mechanism with the same throughput is maintained until the third

and fourth jump, but lost 10% superiosres video, making the video encoding is not

complete with myEvalSVC Framework.

These results show that the transmission H.264/SVC on EDCA can achieve better

PSNR values of the transmission through DCF, illustrating how the throughput and

delay as a function of the number of hops can be percevida by the end user, through the

effects visual myEvalSVC the Framework allows for the recostruir video lens or

receiving node. This feature is one that highlights the myEvalSVC Framework as a tool

for evaluation of QoE, for an end user, which can visually compare the performance of

the video in a different network topologies.Increasing delay and throughput decrease with increasing number of hops,

concludes that the video can be decoded H.264SVC rates 10% lower losses in the case

of DCF, EDCA provides QoS while Ad Hoc Network 3 and 4 hops for the particular case

of 50 nodes that maintain a constant speed of 6m / s and with 8 nodes act as traffic

sources with their respective target nodes/receiver.


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Evaluation of QoS and QoE for H.264/SVC Video Transmission with DCF and EDCA