1. Multicast Tree Reconfiguration in Distributed Interactive Applications Pål Halvorsen 1,2, Knut-Helge Vik 1 and Carsten Griwodz 1,2 1 Department of Informatics, University of Oslo, Norway 2 Simula Research Laboratory, Norway

2. 2005 Pål Halvorsen, Knut-Helge Vik & Carsten Griwodz NIME’ 06, Las Vegas, NV, USA. Januar 2006 Game environment Typical massive multiplayer online games today Central server-based Experience high latency Physical world and virtual world locality are unrelated Real-World Proximity Virtual World Proximity

3. 2005 Pål Halvorsen, Knut-Helge Vik & Carsten Griwodz NIME’ 06, Las Vegas, NV, USA. Januar 2006 Game environment Example: 1 hour trace of one region of Anarchy Online Here: Most action in Europe At other times of day the center of action shifts Average latency could be reduced considerably North America Europe Asia

4. 2005 Pål Halvorsen, Knut-Helge Vik & Carsten Griwodz NIME’ 06, Las Vegas, NV, USA. Januar 2006 Reducing the worst-case latency For average area of interest: find a node that improves average latency Let this “leader” node handle state on behalf of the server Variation of the central server approach Remaining problem: Network utilization This leader node is probably less powerful than the server Games traffic is not adaptive S Transfer state L

5. 2005 Pål Halvorsen, Knut-Helge Vik & Carsten Griwodz NIME’ 06, Las Vegas, NV, USA. Januar 2006 Non-adaptive games traffic Games traffic: UDP or TCP UDP is not adaptive TCP games traffic is not either !!! Games connections are so thin that TCP’s congestion control does not apply We should conserve network resources Number of packets per round-trip time

6. 2005 Pål Halvorsen, Knut-Helge Vik & Carsten Griwodz NIME’ 06, Las Vegas, NV, USA. Januar 2006 Reducing tree cost Tree structure saves resources Alleviates the communication overhead Best results: Minimum Spanning Tree (MST) or Steiner Minimum Tree (SMT) Tree computation necessary for each join and leave MST and SMT computations are Too slow Usually centralized Need fast heuristics S n Lower worst-case delay Transfer state L New node enters L

7. 2005 Pål Halvorsen, Knut-Helge Vik & Carsten Griwodz NIME’ 06, Las Vegas, NV, USA. Januar 2006 Various Join operations all LEAVE operations: remain in the graph until degree is 2 or less

8. 2005 Pål Halvorsen, Knut-Helge Vik & Carsten Griwodz NIME’ 06, Las Vegas, NV, USA. Januar 2006 Effects of Join operations Tested on several topologies generated using BRITE Here: several iterations of groups with Zipf-distributed popularities Time for entering a group Sum of all edge delays When groups are small  complex algorithms are faster than simple ones  complex algorithms provide better results

9. 2005 Pål Halvorsen, Knut-Helge Vik & Carsten Griwodz NIME’ 06, Las Vegas, NV, USA. Januar 2006 Effects of Join operations Tested on several topologies generated using BRITE Here: several iterations of groups with Zipf-distributed popularities Time for entering a group Sum of all edge delays When groups are large and constantly changing  “connect best” takes too long without any performance gain  cost of more complex algorithms decreases quickly

10. 2005 Pål Halvorsen, Knut-Helge Vik & Carsten Griwodz NIME’ 06, Las Vegas, NV, USA. Januar 2006 Effects of Join operations Tested on several topologies generated using BRITE Here: several iterations of groups with Zipf-distributed popularities Time for entering a group Sum of all edge delays When groups are very large and constantly changing  nearly all nodes remain in the graph because we do allow nodes to leave only when they 2 or fewer neighbors

11. 2005 Pål Halvorsen, Knut-Helge Vik & Carsten Griwodz NIME’ 06, Las Vegas, NV, USA. Januar 2006 Conclusions Join operation by itself is not sufficient to define a tree Fast join operation is preferable for small groups Cost-conscious join operations are preferable for large groups Currently investigating Minimum Spanning Tree and Steiner Tree Heuristics Goal is to evaluate some that are Distributed and Dynamic Compare then with simple Join approaches Future work Resilience through pre-defined backup paths