1. Vikash Agarwal, Reza Rejaie Computer and Information Science Department University of Oregon http://mirage.cs.uoregon.edu January 19, 2005 Adaptive Multi-Source Streaming in Heterogeneous Peer-to-Peer Networks

2. Introduction P2P streaming becomes increasingly popular Participating peers form an overlay to cooperatively stream content among themselves Overlay-based approach is the only way to efficiently support multi-party streaming apps without multicast Two components: Overlay construction Content delivery Each peer desires to receive max. quality that can be streamed through its access link Peers have asymmetric & heterogeneous BW connectivity  Each peer should receive content from multiple parent peers => Multi-source streaming.  Multi-parent overlay structure rather than tree

3. Benefits of Multi-source Streaming Higher bandwidth to each peer higher delivered quality Better load balancing among peers Less congestion across the network More robust to dynamics of peer participation  Multi-source streaming introduces new challenges …

4. Multi-source streaming: Challenges Congestion controlled connections from different parent peers exhibit independent variations in BW different RTT, BW, loss rate Aggregate bandwidth changes over time  Streaming mechanism should be quality adaptive Static “one-layer-per-sender” approach is inefficient There must be a coordination mechanism among senders in order to Efficiently utilize aggregate bandwidth Gracefully adapt delivered quality with BW variations This paper presents a receiver-driven coordination mechanism for multi-source streaming called PALS

5. Previous Studies Congestion control was often ignored Server/content placement for streaming MD content [Apostolopoulos et al.] Resource management for P2P streaming [Cue et al.] Multi-sender streaming [Nguyen et al], but they assumed Aggregate BW is more than stream BW RLM is receiver-driven but.. RLM tightly couples coarse quality adaptation with CC PALS only determines how aggregate BW is used P2P content dist. mechanism can not accomodate “streaming” apps e.g. BitTorrent, Bullet

6. Overall Architecture Overall architecture for P2P streaming PRO: Bandwidth-aware overlay construction Identifying good parents in the overlay PALS: Multi-source adaptive streaming Streaming content from selected parents Distributed multimedia caching Decoupling overlay construction from delivery provides great deal of flexibility PALS is a generic multi-source streaming protocol for non-interactive applications

7. Assumptions & Goals Assumptions: All peers/flows are cong. controlled Content is layered encoded All layers are CBR with the same cons. rate* All senders have all layers (relax this later)* Limited window of future packets are available at each sender Live but non-interactive * Not requirements Goals: To fully utilize aggregate bandwidth to dynamically maximize delivered quality Deliver max no of layers Minimize variations in quality

8. P2P Adaptive Layered Streaming (PALS) Receiver: periodically requests an ordered list of packets/segments from each sender. Sender: simply delivers requested packets with the given order at the CC rate Benefits of ordering the requested list: Provide flexibility for the receiver to closely control delivered packets Graceful degradation in quality when bandwidth suddenly drops Periodic requests => stability & less overhead

9. Basic Framework Internet Peer 0 bw (t) 2 1 CCC buf 1 2 bw (t) 3 3 buf Decoder Demux C buf 0 bw (t) 0 BW 0 1 2 Peer 1 Peer 2 Receiver passively monitors EWMA BW from each sender  EWMA aggregate BW  Estimate total no of pkts to be delivered during next window (K) Allocate K pkts among active layers (Quality Adaptation) Controlling bw0(t), bw1(t), …, Controlling evolution of buf. state. Assign a subset of pkts to each sender (Packet assignment) Allocating each sender’s bw among active layers

10. Key Components of PALS Sliding Window (SW): to keep all senders busy & loosely synchronized with receiver playout time Quality adaptation (QA): to determine quality of delivered stream, i.e. required packets for all layers during one window Packet Assignment (PA): to properly distribute required packets among senders

11. Sliding Window Buffering window: range of timestamps for packets that must be requested in one window. Window is slided forward in a step-like fashion Requested packets per window can be from 1) Playing window (loss recovery) 2) Buffering window (main group) 3) Future windows (buffering)

12. Sliding Window (cont’d) Window size determines the tradeoff between smoothness or signaling overhead & responsiveness Should be a function of RTT since it specifies timescale of variations in BW Multiple of max smoothed RTT among senders Receiver might receive duplicates Re-requesting the packet that is in flight! Ratio of duplicates are very low and can be reduced by increasing window

13. Coping with BW variations Sliding window is insufficient Coping with sudden drop in BW by Overwriting request at senders Ordering requested packets Coping with sudden increase in BW by Requesting extra packets

14. Quality Adaptation Determining required packets from future windows Coarse-grained adaptation Add/drop layer Fine-grained adaptation Controlling bw0(t), bw1(t), …, Loosely controlling evolution of receiver buffer state/dist. What is a proper buffer dist?  Buffer distribution determines what degree of BW variations can be smoothed. Internet Peer 0 bw (t) 2 1 CCC buf 1 2 bw (t) 3 3 buf Decoder Demux C buf 0 bw (t) 0 BW 0 1 2 Peer 1 Peer 2

15. Buffer Distribution Impact on delivered quality Conservative buf. distribution achieves long-term smoothing Aggressive buf. distribution achieves short-term improvement PALS leverages this tradeoff in a balanced fashion Window size affects buffering: Amount of future buffering Slope of buffer distribution Multiple opportunities to request a packet (see paper) Implicit loss recovery

16. Packet Assignment How to assign an ordered list of selected pkts from diff. layers to individual senders? Number of assigned pkts to each sender must be proportional to its BW contribution More important pkts should be delivered  Weighted round robin pkt assignment strategy Extended this strategy to support partially available content at each peer Please see paper for further details

17. Performance Evaluation Using ns simulation to control BW dynamics Focused on three key dynamics in P2P systems: BW variations, Peer participation, Content availability Senders with heterogeneous RTT & BW Decouple underlying CC mechanism from PALS Performance Metrics: BW Utilization, Delivered Quality Two strawman mechanisms with static layer assignment to each sender: Single Layer per Sender (SLS): Sender i delivers layer i Multiple Layer per Sender (MLS): Sender i delivers layer j<i

18. Necessity of Coordination SLS & MLS exhibit high variations in quality No explicit loss recovery No coordination Inter-layer dependency magnifies the problem PALS effectively utilizes aggregate BW & delivers stable quality in all cases

19. Delay-Window Tradeoff Avg. delivered quality only depends on agg. BW Heterogeneous senders Higher Delay => smoother quality Duplicates exponentially decrease with window size Avg. per-layer buffering linearly increases with Delay Increasing window leads to even buffer dist. See paper for more results.

20. Conclusion & Future Work PALS is a receiver-driven coordination mechanism for streaming from multiple cong. controlled senders. Simulation results are very promising Future work: Further simulation to examine further details Prototype implementation for real experiments Integration with other components of our architecture for P2P streaming

21. Partially available content Effect of segment size and redundancy

24. Packet Dynamics