1. Peer-to-Peer Support for Massively Multiplayer Games Bjorn Knutsson, Honghui Lu, Wei Xu, Bryan Hopkins Presented by Mohammed Alam (Shahed)

2. 2 Outline Introduction Overview of MMG Peer-to-Peer Infrastructure Distributed Game Design Game on P2P overlay Experimental Results Future Work and Discussion

3. 3 Outline Introduction Overview of MMG Peer-to-Peer Infrastructure Distributed Game Design Game on P2P overlay Experimental Results Future Work and Discussion

4. 4 Introduction Proposes use of P2P overlays to support Massively multiplayer games (MMG) Primary contribution of paper: –Architectural (P2P for MMG) –Evaluative

5. 5 Introduction PASTRY (P2P overlay) SCRIBE (Multicast support) MMG GAME

6. 6 Introduction Players contribute memory, CPU cycles and bandwidth for shared game state Three potential problems: –Performance –Availability –security

7. 7 Outline Introduction Overview of MMG Peer-to-Peer Infrastructure Distributed Game Design Game on P2P overlay Experimental Results Future Work and Discussion

8. 8 Overview of MMG Thousands of players co-exist in same game world Most MMG’s are role playing games (RPG) or real-time strategy(RTS) or hybrids Examples: Everquest, Ultima online, Sims online

9. 9 Overview of MMG GAME STATES World made up of -immutable landscape information (terrain) -Characters controlled by players -Mutable objects (food, tools, weapons) -Non-player characters (NPCs) controlled by automated algorithms

10. 10 Overview of MMG GAME STATES (contd..) –Game world divided into connected regions –Regions on different servers Regions further divided to keep data in memory small

11. 11 Overview of MMG EXISTING SYSTEM SUPPORT –Client-server architecture Server responsible for –Maintain & disseminate game state –Account management & authentication Scalability achieved by –Dedicated servers –Clustering servers »LAN or computing grid

12. 12 Overview of MMG Latency –Varies –Guiding ‘avatars’ tolerates more latency –First person shooter games (180 millisecond latency max) –Real time strategy (several seconds)

13. 13 Outline Introduction Overview of MMG Peer-to-Peer Infrastructure Distributed Game Design Game on P2P overlay Experimental Results Future Work and Discussion

14. 14 Peer-to-Peer Infrastructure PASTRY (P2P overlay) SCRIBE (Multicast support) MMG GAME

15. 15 Outline Introduction Overview of MMG Peer-to-Peer Infrastructure Distributed Game Design Game on P2P overlay Experimental Results Future Work and Discussion

16. 16 Distributed Game Design

17. 17 Distributed Game Design Persistent user state is centralized –Example: payment information, character Allows central server to delegate bandwidth and process intensive game state to peers

18. 18 Distributed Game Design Game design based on fact that: –Players have limited movement speed –Limited sensing capability –Hence data shows temporal and spatial localities –Use Interest Management Limit amount of state player has access to

19. 19 Distributed Game Design Players in same region form interest group State updates relevant to group disseminated only within group Player changes group when going from region to region

20. 20 Distributed Game Design GAME STATE CONSISTENCY –Must be consistent among players in a region –Basic approach: employ coordinators to resolve update conflicts –Split game state management into three classes to handle update conflicts: Player state Object state The Map

21. 21 Distributed Game Design Player state –Single writer multiple reader –Player-player interaction effects only the 2 players involved –Position change is most common event Use best effort multicast to players in same region Use dead reckoning to handle loss or delay

22. 22 Distributed Game Design Object state –Use coordinator-based mechanism for shared objects –Each object assigned a coordinator –Coordinator resolves conflicting updates and keeps current value

23. 23 Outline Introduction Overview of MMG Peer-to-Peer Infrastructure Distributed Game Design Game on P2P overlay Experimental Results Future Work and Discussion

24. 24 Game on P2P overlay Map game states to players –Group players & objects by region –Map regions to peers using pastry Key –Each region is assigned ID –Live Node with closest ID becomes coordinator –Random Mapping reduces chance of coordinator becoming member of region (reduces cheating) –Currently all objects in region coordinated by one Node –Could assign coordinator for each object

25. 25 Game on P2P overlay Shared state replication –Lightweight primary- backup to handle failures –Failure detected using regular game events –Dynamically replicate coordinator when failure detected –Keep at least one replica at all times –Uses property of P2P (route message with key K to node ID, N, closest to K)

26. 26 Game on P2P overlay Shared state replication (contd..) –The replica kept at M which is the next closest to message or object K – If new node added which is closer to message K than coordinator Forwards to coordinator Updates itself Takes over as coordinator

27. 27 Game on P2P overlay Catastrophic failure –Both coordinator and replica dead –Problem solved by cached information from nodes interested in area

28. 28 Outline Introduction Overview of MMG Peer-to-Peer Infrastructure Distributed Game Design Game on P2P overlay Experimental Results Future Work and Discussion

29. 29 Experimental Results Prototype Implementation of “SimMud” Used FreePastry (open source) Maximum simulation size constrained by memory to 4000 virtual nodes Players eat and fight every 20 seconds Remain in a region for 40 seconds Position updates every 150 millisec by multicast

30. 30 Experimental Results Base Results –No players join or leave –300 seconds of game play –Average 10 players per region –Link between nodes have random delay of 3-100 ms to simulate network delay

31. 31 Experimental Results (Base results)

32. 32 Experimental Results (Base results) 1000 to 4000 players with 100 to 400 regions Each node receives 50 –120 messages 70 update messages per second –10 players * 7 position updates Unicast and multicast message take around 6 hops

33. 33 Experimental Results (Base results)

34. 34 Experimental Results Breakdown of type of messages –99% messages are position updates –Region changes take most bandwidth –Message rate of object updates higher than player-player updates Object updates multicast to region Object update sent to replica Player player interaction effects only players

35. 35 Experimental Results Effect of Population Growth –As long as average density remains same, population growth does not make difference Effect of Population Density –Ran with 1000 players, 25 regions –Position updates increases linearly per node –Non – uniform player distribution hurts performance

36. 36 Experimental Results Three ways to deal with population density problem –Allow max number of players in region –Different regions have different size –System dynamically repartitions regions with increasing players

37. 37 Experimental Results Effect of message aggregation –Since updates are multicast, aggregate them at root –Position update aggregated from all players before transmit –Cuts bandwidth requirement by half –Nodes receive less messages

38. 38 Experimental Results

39. 39 Experimental Results

40. 40 Experimental Results Effect of network dynamics –Nodes join and depart at regular intervals –Simulate one random node join and depart per second –Per-node failure rate of 0.06 per minute –Average session length of 16.7 minutes (close to 18 minutes for half life) –Average message rate increased from 24.12 to 24.52 –Catastrophic failure every 20 hours

41. 41 Outline Introduction Overview of MMG Peer-to-Peer Infrastructure Distributed Game Design Game on P2P overlay Experimental Results Future Work and Discussion

42. 42 Future Work Assumes uniform latency for now Testing games with more states and on global distributed network platforms Stop cheating by detection

43. 43 Discussion Assigning random coordinators could hurt in P2P (modem vs high-speed) How close can the results obtained in simulation on one machine work in real Given range of 7.2kB/sec – 22.34 KB/sec in easy game. What about games with more states How would aggregating messages be bad? –In their case waits for all messages to come before sending? Latency issues?