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Network-adaptive Rate and Error Control for Video Streaming over Wireless Multi-hop Networks Jung tae Bae Netmedia Lab. Lab seminar (2009.05.30) 1.

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Presentation on theme: "Network-adaptive Rate and Error Control for Video Streaming over Wireless Multi-hop Networks Jung tae Bae Netmedia Lab. Lab seminar (2009.05.30) 1."— Presentation transcript:

1 Network-adaptive Rate and Error Control for Video Streaming over Wireless Multi-hop Networks Jung tae Bae Netmedia Lab. Lab seminar ( ) 1

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 2

3 Introduction Wireless multi-hop networks (WMNs) –A cheap and efficient method for providing network connectivity 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 3

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 scalability) Base layer: l1, enhancement layers: l2, l3, …, ln After video rate adaptation, k video layers are transmitted SRN1N2N3 N5 N7N6 N4 Source video stream Adapted video stream Video adaptation 4

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? SRN1N2N3 B1 Be video flow background flow time-varying network available bandwidth 5

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 6

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 intermediate hop –Additional overhead Control overhead Computational complexity and per-delay due to FEC encoding/decoding 7

8 Contributions 1. Hybrid E2E and HbH approach 3. Implement and experiment in real testbed 2. Rate and error control based on partition QoS control ServerReceiver Rate/error control Intermediate node 8 Path partition algorithm

9 Proposed System Architecture 9

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 10

11 Hybrid E2E and HbH Approach Architecturally, this flexibly lies between E2E and HbH Approach Select control node among intermediate nodes according to network status. Control nodes control video sending rate and error. How to select control node? => Path partition algorithm ServerReceiver Intermediate node CONTROL NODE 11

12 Path Partitioning Congestion Congested or uncongested? Reliable or unreliable? Congestion unreliable : Control node (CN) (P partition1, d partition1 )(P partition2, d partition2 ) (P partition3, d partition3 ) (P partition4, d partition4 )(P partition5, d partition5 ) 12

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 uncongested? –Congestion status is required to determine the network state –Based on expectation of buffer overflow at a node –If queue length, q l > queue threshold, q thr, then link is congested. 13

14 Monitoring Reliable or unreliable? –MAC packet loss rate The ratio of the number of discarded video packets at MAC layer interface queue over the number of total video packets arrived at the queue By using smooth function P = α * P + (1-α)*P sampleloss Where P sampleloss Where is packet loss rate per a constant time. –If P i > p thr,, the link is unreliable –Use probe packet P1P1 P1P1 P2P2 1-(1-P 1 ) (1-P 2 ) 14

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 approach) 15

16 Rate and Error Control based on Partition Two control node in Partition Selectively use rate and error control according status in partition Partition 1Partition 2Partition 3 Rate/error control 16

17 Partition State Each partition S i can be in one of the following state –S i {State #1, State #2, State #3, State #4} State #1: (no congestion, high reliability) –q l < q thr, p < p thr –Ideal state State #2: (no congestion, low reliability) –q l p thr –Increase error control level –Use error control mode with more high error recovery performance State #3: (congestion, high reliability) –q l > q thr, p < p thr –Reduce the video sending rate (rate control) State #4: (congestion, low reliability) –q l > q thr, p > p thr –Reduce the video sending rate (rate control) –Increase error control level –Use error control mode with more high error recovery performance 17

18 Rate Control Transfer lower video sending rate (k send ) 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 18

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 r k is the maximum number of retransmission of packet k Parameters p the probability of transport packet loss T0T0 the transmission delay constraint of fram es RTRT transmission rate BpBp total bits per packet d par ittion Delay at partition drdr delay between control node and receiver 19

20 Error Control Optimized error control mode selection –FEC Parameters p the probability of transport packet loss T0T0 the transmission delay constraint of frames RTRT transmission rate BpBp total bits per packet d parit tion Delay at partition d4d4 delay between control node and receiver 20

21 Error Control Optimized error control mode selection –HARQ Parameters p the probability of transport packet loss T0T0 the transmission delay constraint of frames RTRT transmission rate BpBp total bits per packet d parit tion Delay at partition d4d4 delay between control node and receiver NeNe The number of lost packet (N e > n-k) 21

22 Experimental Setup Deployed in GIST DIC 2nd floor 1 Server (N1), 6 Intermediate nodes (N2~N7), 1 Receiver (N8) IEEE a-based single interface 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 22

23 Experimental Results (1/2) 23 Path partition algorithm

24 Experimental Results (2/2) E2E packet loss rate (%) Packet loss rate (E2E) Packet loss rate ( HBH) Packet loss rate ( Proposed) The average numb er of partitions

25 Conclusions Proposed network adaptive rate and error control for video streaming over wireless multi-hop networks 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 25


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