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1 Failure Recovery for Priority Progress Multicast Jung-Rung Han Supervisor: Charles Krasic.

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Presentation on theme: "1 Failure Recovery for Priority Progress Multicast Jung-Rung Han Supervisor: Charles Krasic."— Presentation transcript:

1 1 Failure Recovery for Priority Progress Multicast Jung-Rung Han Supervisor: Charles Krasic

2 2 Multicast? One-to-Many delivery One-to-Many delivery scalable scalable conserve bandwidth conserve bandwidth E.g. Digital TV E.g. Digital TV IP multicast IP multicast Many issues: security, billing, money Many issues: security, billing, money Application level multicast Application level multicast Dedicated content distribution network Dedicated content distribution network Peer-to-Peer / End system multicast Peer-to-Peer / End system multicast

3 3 QStream Priority Progress Streaming (PPS) Adaptive to network conditions Adaptive to network conditions Using TCP Using TCP Speg: Scalable mpeg, a “ progressive ” codec Speg: Scalable mpeg, a “ progressive ” codec Priority Progress Multicast (PPM) Priority Progress Multicast (PPM) Makes a tree of PPS Makes a tree of PPS

4 4 Priority Progress Multicast Store-and-Forward Store-and-Forward Fragments data Fragments data Flow control Flow control Single tree multicast Single tree multicast

5 5 Presentation Outline Motivation Motivation Background Background Description of Approach Description of Approach Evaluation Evaluation Conclusions and Future Work Conclusions and Future Work

6 6 Motivation: Single Tree vs. Graph Multicast Single tree Advantages Advantages Simpler Simpler Less overhead Less overhead Disadvantages Disadvantages Vulnerable to failure Vulnerable to failure Unutilized bandwidth Unutilized bandwidth Graph Advantages Resilient to failure Higher bandwidth utilization Disadvantages More overhead Complex Hard to implement Hidden issues

7 7 Presentation Outline Motivation Motivation Background Background Description of Approach Description of Approach Evaluation Evaluation Conclusions and Future Work Conclusions and Future Work

8 8 Background: Some multicast “ streaming ” systems QStream: Single Tree Based QStream: Single Tree Based Bullet: Bullet: Single Tree as backbone, Peering connections form Mesh Single Tree as backbone, Peering connections form Mesh SplitStream: SplitStream: Multiple Trees Multiple Trees

9 9 SplitStream

10 10 Presentation Outline Motivation Motivation Background Background Description of Approach Description of Approach Evaluation Evaluation Conclusions and Future Work Conclusions and Future Work

11 11 Distributed Tree Management Tree Join operation, Tree Join operation, also dealing with failure Key issues: Scalability, Delay, Security … Key issues: Scalability, Delay, Security … Our approach: use Distributed Hash Table (DHT) Our approach: use Distributed Hash Table (DHT) Bamboo DHT and ReDiR Hierarchy Bamboo DHT and ReDiR Hierarchy (Recursive Distributed Rendezvous) Reuse one DHT for all mcast session. Removes hotspot when nodes join at the same time Reuse one DHT for all mcast session. Removes hotspot when nodes join at the same time

12 12 Failure Recovery Failure: a node in multicast tree disappears Failure: a node in multicast tree disappears Important to Single tree approach Important to Single tree approach Less important to multi-source. Less important to multi-source. Our goal: hide the impact of failure Our goal: hide the impact of failure Ultimately, no pause in video playback Ultimately, no pause in video playback Our approach: pre-emptively deal with failure to select a replacement with highest Eligibility. Our approach: pre-emptively deal with failure to select a replacement with highest Eligibility.

13 13 “ Eligibility ” A node ’ s capability to be a good forwarding node. A node ’ s capability to be a good forwarding node. Bandwidth, delay, uptime, distance from the root, etc. Bandwidth, delay, uptime, distance from the root, etc. This is another sub-area of research that deals with predicting and evaluating the quality of a connection that is inherently variable. Vivaldi, iPlane This is another sub-area of research that deals with predicting and evaluating the quality of a connection that is inherently variable. Vivaldi, iPlane

14 14 Eligibility propagation Goal: a node has replacement for its parent, based on eligibility information Goal: a node has replacement for its parent, based on eligibility information Only allows leaf node to be a replacement candidate. Only allows leaf node to be a replacement candidate. A leaf node ’ s eligibility propagates up A leaf node ’ s eligibility propagates up All internal node keeps track of the highest leaf node reported from downstream and select a replacement for itself All internal node keeps track of the highest leaf node reported from downstream and select a replacement for itself Report the chosen node to its direct children Report the chosen node to its direct children

15 15 Now we know what to do when a failure occurs But we still need something …

16 16 Failure Detection TCP ’ s failure detection is inadequate TCP ’ s failure detection is inadequate Application level heartbeat Application level heartbeat Heartbeat interval is major concern Heartbeat interval is major concern False positive vs. Delay False positive vs. Delay TCP vs. UDP heartbeat TCP vs. UDP heartbeat

17 17 Presentation Outline Motivation Motivation Background Background Description of Approach Description of Approach Evaluation Evaluation Conclusions and Future Work Conclusions and Future Work

18 18 Evaluation Multi-dimensional test space: Multi-dimensional test space: Roundtrip Time Roundtrip Time Heartbeat interval Heartbeat interval Competing traffic Competing traffic Wide vs. Narrow tree Wide vs. Narrow tree Long vs. Short tree Long vs. Short tree Failure rate Failure rate Adaptation window size Adaptation window size Different video quality metrics Different video quality metrics

19 19 Emulab www.emulab.net www.emulab.net www.emulab.net Network testbed Network testbed Hundreds of machines Hundreds of machines Allows users high degree of freedom Allows users high degree of freedom Network topology Network topology Traffic shaping: BW, delay, loss rate Traffic shaping: BW, delay, loss rate OS modifications OS modifications All done through web interface and SSH All done through web interface and SSH

20 20 Minimum Tree – Emulab Topology

21 21 Minimum Tree – Multicast Tree

22 22 Minimum Tree – BW graph

23 23 Medium Size Tree – Emulab Topology

24 24 Medium Size Tree – Multicast

25 25 Medium Size Tree – BW graph

26 26 Presentation Outline Motivation Motivation Background Background Description of Approach Description of Approach Evaluation Evaluation Conclusions and Future Work Conclusions and Future Work

27 27 Conclusions A single tree approach can deal with failures (probably) A single tree approach can deal with failures (probably) Video playback is not interrupted Video playback is not interrupted Impact of failure is second order concern to TCP dynamics Impact of failure is second order concern to TCP dynamics Many other evaluations can be done Many other evaluations can be done Different BW and RTT Different BW and RTT Bigger tree Bigger tree Varying degree of competing traffic Varying degree of competing traffic Higher failure rate Higher failure rate

28 28 Future Work Evaluation of Distributed Tree Management approach Evaluation of Distributed Tree Management approach Continued evaluation of failure recovery under different conditions Continued evaluation of failure recovery under different conditions Self adjusting tree to optimize bandwidth usage Self adjusting tree to optimize bandwidth usage Scaling window size Scaling window size

29 29 Final Comment Evaluating the system is hard Evaluating the system is hard Many variables Many variables Unexpected results Unexpected results Using Emulab Using Emulab Availability affected by time of day and paper submission deadline Availability affected by time of day and paper submission deadline Nodes do malfunction: do linktest often, but takes significantly longer with bigger experiment! Nodes do malfunction: do linktest often, but takes significantly longer with bigger experiment! One run of an experiment takes 25 minutes One run of an experiment takes 25 minutes Tip: Use a lot of scripts! Tip: Use a lot of scripts!

30 30 ReDirReDirReDirReDir


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