Jung tae Bae Netmedia Lab.

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

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 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

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 N4 N5 Source video stream Adapted video stream S N1 N2 N3 R Video adaptation N6 N7

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? video flow background flow B1 time-varying network available bandwidth S N1 N2 N3 R Be

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 intermediate hop • Additional overhead • Control overhead • Computational complexity and per-delay due to FEC encoding/decoding <FEC redundancy, k=18> <End-to-end packet loss rate>

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

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 HbHApproach • 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 Intermediate node Intermediate node Intermediate node Server Receiver Intermediate node Intermediate node CONTROL NODE

12. Path Partitioning Congested or uncongested? Congestion Congestion Reliable or unreliable? unreliable Congestion Congestion (Ppartition1, dpartition1) (Ppartition2, dpartition2) (Ppartition4, dpartition4) (Ppartition5, dpartition5) (Ppartition3, dpartition3) : Control node (CN)

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, 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 interface 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 1-(1-P1) (1-P2) P1 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 approach)

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 Sican 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

20. Error Control • Optimized error control mode selection • FEC

21. Error Control • Optimized error control mode selection • HARQ

22. Experimental Setup • Deployed in GIST DIC 2nd floor • 1 Server (N1), 6Intermediate nodes (N2~N7), 1 Receiver (N8) • IEEE 802.11a-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 <Node deployment of testbed>

23. Experimental Results (1/2) • Path partition algorithm • <Packet loss rate> • <The number of partitions>

24. Experimental Results (2/2) • <Packet loss rate after control> • <Discontinuity>

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