1

Network-adaptive Rate and Error Control for Video Streaming

over Wireless Multi-hop Networks

Jung tae BaeNetmedia Lab.

Lab seminar (2009.05.30)

2

Contents

• Introduction and Background• Contributions• Network adaptive rate and error control for video

streaming over wireless multi-hop networks– Hybrid E2E and HbH Approach – Path Partition Algorithm– Rate and Error Control based on Partition

• Experimental Results• Conclusions

3

Introduction• Wireless multi-hop networks (WMNs)

– A cheap and efficient method for providing network connectiv-ity

• Challenges of video streaming over WMNs– Random channel error– Scarce and time-varying network available bandwidth

• Dynamic channel capacity due to various kinds of interference• As increasing hop-count, end-to-end throughput is severely degraded

=> packet losses at receiver.

• Our solutions to reduce packet losses: – Error control (FEC, ARQ, etc.)– Video rate control

4

Problem Description (1/2)

• Basic Assumptions– A video flow use a single path in WMNs

– A video flow can be transmitted in scalable fashion (e.g., temporal scal-ability)• Base layer: l1, enhancement layers: l2, l3, …, ln• After video rate adaptation, k video layers are transmitted

S RN1 N2 N3

N5

N7N6

N4

Source video stream

3l2l1l

nl

1l

2l

kl

Adapted video stream

Video adaptation

5

Problem Description (2/2)

• Interference due to competing flow– Network available bandwidth for video flow is fluctuating– Arbitrary Intra-/Inter-background flow

• For the given assumptions,– How to minimize the impact of packet losses according to

time-varying networks status to improve end-to-end video quality?

S RN1 N2 N3

B1

Be

video flowbackground flow

time-varying network available bandwidth

6

Background (1/2)• Two approach for rate and error control

– End-to-End approach– Hop-by-hop approach

• End-to-End approach

– Control node: only sender – End-to-end feedback– Delay of feedback makes that adaptation reacts slowly to time-varying

channel condition

7

Background (2/2)– Receiver experiences accumulated packet losses

• A number of redundancy for reliability (high bandwidth overhead)• Many retransmission

• Hop-by-hop approach

– Link statistics monitoring (e.g., MAC-layer loss rate) at each intermedi-ate hop

– Additional overhead• Control overhead• Computational complexity and per-delay due to FEC encoding/decoding

<End-to-end packet loss rate> <FEC redundancy, k=18>

8

Contributions

1. Hybrid E2E and HbH ap-proach

3. Implement and experiment in real testbed

2. Rate and error con-trol based on partition

QoS control QoS control QoS control

Server Receiver

Rate/error controlRate/error controlRate/error control

Intermediate nodeIntermediate node

Intermediate nodeIntermediate nodeIntermediate node

Path partition algo-rithm

9

Proposed System Architecture

10

NASTE+ Module• Extension of network-adaptive selection transport error control (NASTE )in

WLAN into Hop-by-Hop Framework in WMNs In each intermediate node, video rate/error control and monitoring functionalities are added

– Rate and error control– Network adaptation manager

• Path partitioning• Select suitable rate and error control mode

– Monitoring• Cross-layer monitoring• Monitoring based on feedback

11

Hybrid E2E and HbH Approach • Architecturally, this flexibly lies between E2E and HbH Approach • Select control node among intermediate nodes according to net-

work status.

• Control nodes control video sending rate and error.• How to select control node?

=> Path partition algorithm

Server ReceiverIntermediate nodeIntermediate node

Intermediate nodeIntermediate nodeIntermediate node

CONTROL NODE

12

Path Partitioning

Congestion Congestion

Congested or un-congested?

Reliable or unreli-able? CongestionCongestionunreliable

: Control node (CN)

(Ppartition1, dpartition1) (Ppartition2, dpartition2) (Ppartition3, dpartition3) (Ppartition4, dpartition4) (Ppartition5, dpartition5)

13

Monitoring

• Loss rate of video stream and queue length are at the local channel measured

• For this, a per-flow state table is maintained

• Congested or uncon-gested?– Congestion status is required

to determine the network state

– Based on expectation of buf-fer overflow at a node

– If queue length, ql > queue threshold, qthr , then link is congested.

14

Monitoring

• Reliable or unreliable?– MAC packet loss rate

• The ratio of the number of discarded video packets at MAC layer in-terface queue over the number of total video packets arrived at the queue

• By using smooth function P = α * P + (1-α)*Psampleloss

Where Psampleloss Where is packet loss rate per a constant time.

– If Pi > pthr,, the link is unreliable

– Use probe packet

P1

P1 P2

1-(1-P1) (1-P2)

15

Path Partition Algorithm

• The largest partition could include all the nodes of the network path (same as the end-to-end approach),

• The smallest partition could be one hop (i.e. hop-by-hop ap-proach)

16

Rate and Error Control based on Partition

• Two control node in Partition • Selectively use rate and error control according status in

partition

Partition 1 Partition 2 Partition 3

Rate/error control Rate/error control Rate/error control

17

Partition State• Each partition Si can be in one of the following state

– Si ∈ {State #1, State #2, State #3, State #4}

• State #1: (no congestion, high reliability)– ql < qthr, p < pthr

– Ideal state

• State #2: (no congestion, low reliability)– ql < qthr, p > pthr

– Increase error control level– Use error control mode with more high error recovery performance

• State #3: (congestion, high reliability)– ql > qthr, p < pthr

– Reduce the video sending rate (rate control)

• State #4: (congestion, low reliability)– ql > qthr, p > pthr

– Reduce the video sending rate (rate control)– Increase error control level– Use error control mode with more high error recovery performance

18

Rate Control

• Transfer lower video sending rate (ksend) at the detection of congestion.

• Maintain a drop time (DT) for each level.• Intermediate nodes adapt video sending rate to the channel

condition of bottleneck link by comparing the local channel condition and hop feedback information

19

Error Control • Find a suitable mode

– by combining performance each error control mode – according to channel status– 3 error control mode: ARQ, FEC and Hybrid ARQ

• Optimized error control mode selection– Given delay constraints, find error control mode which has error recovery

performance– ARQ

• rk is the maximum number of retransmission of packet k

Parameters

p the probability of transport packet loss

T0the transmission delay constraint of frames

RT transmission rate

Bp total bits per packet

dpar

ittion

Delay at partition

drdelay between control node and re-ceiver

20

Error Control

• Optimized error control mode selection– FEC

D e c o d e rE n c o d e r

sourcepackets

encodedpackets

receivedpackets

reconstructedpackets

k n K >=k k

Parameters

p the probability of transport packet loss

T0the transmission delay constraint of frames

RT transmission rate

Bp total bits per packet

dpari

ttion

Delay at partition

d4delay between control node and re-ceiver

21

Error Control

• Optimized error control mode selection– HARQ

Parameters

p the probability of transport packet loss

T0the transmission delay constraint of frames

RT transmission rate

Bp total bits per packet

dpari

ttion

Delay at partition

d4delay between control node and re-ceiver

Ne The number of lost packet (Ne > n-k)

22

Experimental Setup

<Node deployment of testbed>

• Deployed in GIST DIC 2nd floor• 1 Server (N1), 6 Intermediate

nodes (N2~N7), 1 Receiver (N8)• IEEE 802.11a-based single inter-

face• PHY data rate : 54Mbps• MAC retransmission off• Experimental video

– GOP: IBBPBB, 30fps, 4Mbps– 4 Temporal layers (l1, l2, l3, l4)

• l1: 1.52Mbps, l2: 0.86Mbps, l3: 0.8Mbps, l4: 0.8Mbps

– Frame rate profile of each temporal layer• l1: 5fps, l2: 5fps, l3: 10fps, l4: 10fps

23

Experimental Results (1/2)

<Packet loss rate> <The number of parti-tions>

• Path partition algorithm

24

Experimental Results (2/2)

<Discontinuity><Packet loss rate after con-trol>

E2E packet loss rate (%)

Packet loss rate (E2E)

Packet loss rate (HBH)

Packet loss rate (Proposed)

The average num-ber of partitions

1.61 0 0 0 1.22

5.20 2.1 0 0 2.34

12.3 8.1 3.42 3.41 3.43

18.1 16.28 7.55 7.64 5.13

25

Conclusions

• Proposed network adaptive rate and error control for video streaming over wireless multi-hop net-works

• VS E2E and HbH approach– Compared with E2E approach

• Better performance

– Compared with H2H approach• Use fewer intermediate nodes while still maintain performance of

hop-by-hop approach