Energy-efficient Multicasting of Scalable Video Streams over WiMAX Networks
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Transcript of Energy-efficient Multicasting of Scalable Video Streams over WiMAX Networks
Energy-efficient Multicasting of Scalable Video Streams over WiMAX Networks
Somsubhra Sharangi, Ramesh Krishnamurti, Mohamed Hefeeda,
Senior Member, IEEE
Department of Computer Science, Simon Fraser University, Canada
IEEE Transactions on Multimedia, vol. 13, no. 1, Feb. 2011, pp. 102-115.
Outline
• Introduction
• Motivation
• Problem
• Proposed multicasting algorithm– Substream Selection Algorithm (SSA)
– Energy Efficient Substream Allocation (EESA)
• Simulation
• Conclusion
Introduction
• WiMAX supports various network services.
• One of these services is the Multicast and Broadcast Service (MBS), which can be used to deliver multimedia traffic to large-scale user communities.– Yota Telecom has recently started a mobile TV service with 25
channels over its 10 Mbps mobile WiMAX network.
– UDCast has announced plans for developing broadcast TV service supporting around 50 channels over mobile WiMAX.
Introduction
• Mobile Video Multicast/Broadcast– Mobile TV users to increase by 55% by 2015 [VisionGain10]
• Competing Technologies– LTE MBMS Low Bandwidth⇒
• WiMAX Advantage– High Bandwidth
– Better Video Quality Higher Revenue⇒
Introduction
• Multicast/Broadcast Service Data Area in Downlink Frame
Motivation
• H.264 Scalable Video Coding – Temporal, spatial and quality scalability
– Embedded stream metadata information• Supplementary Enhancement Information (SEI) Message
• Video Quality: measurement of video signal peak signal-to-noise ratio (PSNR)
Layer Data Rate (kbps) Quality (dB)
EL2 589 36.00
EL1 407 34.86
BL 170 32.0
Motivation
• Example of Scalable Videos
Stream s
Sub-stream l
Motivation
Sub-stream l EL l EL l EL l EL l EL l
… EL … EL … EL … EL … EL …
Sub-stream 5
EL 4 EL 4 EL 4 EL 4 EL 4
Sub-stream 4
EL 3 EL 3 EL 3 EL 3 EL 3
Sub-stream 3
EL 2 EL 2 EL 2 EL 2 EL 2
Sub-stream 2
EL 1 EL 1 EL 1 EL 1 EL 1
Sub-stream 1
BL BL BL BL BL
Stream 1 Stream 2 Stream 3 Stream 4 Stream 5
Problem
• This paper focuses on optimally utilizing the WiMAX Multicast/Broadcast Service to stream multiple scalable videos to mobile receivers.– Select the optimal subset of layers from each scalable stream
– Maximize the average quality of all selected substreams
Network Environment
Network Environment
• A number of scalable video streams are available at a WiMAX base station.– Each scalable stream s, 1 s S, has at most L layers.
Name(streams)
1 Layer (sub-stream 1) 2 Layers (sub-stream 2)
Data rate r1 Quality q1 Data rate r2 Quality q2
1 187 3398 380 3615
2 548 3715 824 3845
3 466 3294 848 3468
…
…
r31, rsl: data rate of substream sl q12, qsl: PSNR of substream sl
Network Environment
• The average video quality is maximized within a scheduling window.– The Scheduling window has P frames
– Each frame can accommodate F amount of data and takes time
• Maximum amount of data that can be transmitted within the scheduling window is given as
C = PF
F F F F F F F F F
P frames
Substream Selection Algorithm (SSA)
Substream Selection Algorithm (SSA)
• Let V(s, q) denote the set of substreams from stream 1, …, s– no two substreams are selected from the same stream
– total quality of the selected substreams is q.
Name(streams)
1 Layer (sub-stream 1) 2 Layers (sub-stream 2)
Data rate r1 Quality q1 Data rate r2 Quality q2
1 187 3398 380 3615
2 548 3715 824 3845
3 466 3294 848 3468
V(s, q)= {sl}={11, 22, 32}, where q=3398+3845+3468
Substream Selection Algorithm (SSA)
• Let R(s, q) denote the sum of data rates selected in V(s, q)
Name(streams)
1 Layer (sub-stream 1) 2 Layers (sub-stream 2)
Data rate r1 Quality q1 Data rate r2 Quality q2
1 187 3398 380 3615
2 548 3715 824 3845
3 466 3294 848 3468
R(s, q)= 187+824+848, where q=3398+3845+3468
Substream Selection Algorithm (SSA)
Name(streams)
1 Layer (sub-stream 1) 2 Layers (sub-stream 2)
Data rate r1 Quality q1 Data rate r2 Quality q2
1 187 3398 380 3615
2 548 3715 824 3845
3 466 3294 848 3468C=1500
q= 0 … 3398 … 3615 …
s1 0 187 380
s2 0
s3 0
Substream Selection Algorithm (SSA)
3398
187
3615
380
3715
548
3845
824
Name(streams)
1 Layer (sub-stream 1) 2 Layers (sub-stream 2)
Data rate r1 Quality q1 Data rate r2 Quality q2
1 187 3398 380 3615
2 548 3715 824 3845
3 466 3294 848 3468C=1500
R(1,3398)=187
(total) q=3398
Substream Selection Algorithm (SSA)
3398
187
3615
380
3715
548
3845
824
Name(streams)
1 Layer (sub-stream 1) 2 Layers (sub-stream 2)
Data rate r1 Quality q1 Data rate r2 Quality q2
1 187 3398 380 3615
2 548 3715 824 3845
3 466 3294 848 3468C=1500
R(1,3398)=187
(total) q=3398+3715=7113
R(1,7113)=?R(2,7713)=187+548=735
x 7113
7113
735
Substream Selection Algorithm (SSA)
C=1500
3294
3398
3468
3615
3715
3845
6612
6866
6909
7009
7083
7113
7139
7183
7243
7313
7330
7460
10407
10537
10581
10624
10711
10754
10798
10928
187
380
187
380
548
824
735
1011
928
1204
466
187
848
380
548
824
653
1035
846
1014
1228
735
1290
1359
1011
1872
928
1204
1201
1477
1583
1394
1859
1679
1776
2052
Substream Selection Algorithm (SSA)
C=1500
3294
3398
3468
3615
3715
3845
6612
6866
6909
7009
7083
7113
7139
7183
7243
7313
7330
7460
10407
10537
10581
10624
10711
10754
10798
10928
187
380
187
380
548
824
735
1011
928
1204
466
187
848
380
548
824
653
1035
846
1014
1228
735
1290
1359
1011
1872
928
1204
1201
1477
1583
1394
1859
1679
1776
2052
Substream Selection Algorithm (SSA)
• Lower bound: Q0
• Upper bound: 2Q0
Name(streams)
1 Layer (sub-stream 1) 2 Layers (sub-stream 2)
Data rate r1 Quality q1 Data rate r2 Quality q2
1 187 3398 380 3615
2 548 3715 824 3845
3 466 3294 848 3468 =848-466=382
=3468-3294=174
/ = 0.445
Energy Efficient Substream Allocation (EESA)
Simulation Setup
• Video Encoding: H.264/SVC format
• Channel: 10 MHz
• Modulation: 16-QAM ¾
• TDD frame: 5ms
• Scheduling Window: 1 second= 200 frames
• MBS data area: 50kb
• Average bit rate of substreams: 100kbps ~ 2.5 Mbps
Simulation
• Running Time– (a) Fixed Window Size at 1s
– (b) Fixed number of streams at 20
Simulation
• Resource Utilization
Simulation
• Energy efficiency of the EESA
Simulation
Simulation
• Effect of Receiver Buffer
Conclusion
• This paper proposed energy-efficient multicasting of scalable video streams– Maximize the average video stream quality
– Reduce receiver energy consumption
TheENDThanks for your attention !