Towards Reinterpretation of Interaction Complexity for Load Prediction in Cloud-based MMORPGs

1. Mirko Sužnjević, Maja Matijašević Towards Reinterpretation of Interaction Complexityfor Load Prediction in Cloud-based MMORPGs University of Zagreb Faculty of Electrical Engineering and Computing Department of Telecommunications http://www.fer.unizg.hr/ztel/en/research/research_groups/netmedia

2. Number of players on a server = 4000 Number of players on a server = 4000 Motivation Not the same in terms of load!

3. Outline Introduction Related work Mapping Load prediction Resuts Conclusion and open issues

4. Introduction • Current practices in server organization for MMORPGs: • Sharded worlds (World of Warcraft) • Single worlds (EvE Online) • Problems • Player distribution uniform (in specific shard and between shards) • Player behavior patterns • Unexpected behavior • Highly variable load • Cloud based systems – designed to provide optimal amount of resources for services with variable load

5. Related work • Based on work by Nae and Prodan* • Presented formulas for load estimation (both CPU and memory) in distributed MMOs • Created load prediction based on neural networks • Used Runescape as a case study • Defined complexities for different interactions between entities in MMOs • We map the MMORPG behavior categories to specific complexities * R. Prodan and V. Naea, “Prediction-based real-time resource provisioning for massively multiplayer online games,” Future Generation Computer Systems, vol. 25, pp. 785–793, 2009. V. Nae, A. Iosup, and R. Prodan, “Dynamic resource provisioning in massively multiplayer online games,” IEEE Transactions on Parallel and Distributed Systems, vol. 22, pp. 380–395, 2011.

6. Mapping • Goal - to prove that behavioral information has a significant influence on the system load • Redefined calculation of number of interactions based on properties of the action category

7. Load prediction • Simple history based algorithm • History source – previously developed user behavior simulator • Behaviour simulator implements the model which captures behavior patterns • Easy modification of parameters of the behavior (number of players, duration of each separate action category, arrival and departure rates) • Enables simulation of “extreme” events such as flash mobs and content release • Output in form of a text file listing each performed behaviour: Second:124 Type:Change ID:210 Category:5 CategoryOld:6 Duration:433

8. Load prediction II Second:124164 Type:Change ID:2610 Category:5 CategoryOld:6 Duration:433 • Developed a tool for load prediction • Run by simple algorithm based on pattern periods (e.g., day, week) • The history is divided to intervals (e.g., minutes, hours) • It takes into account the whole history and last period in order to capture both patterns and unusual behavior

9. Results Second:124164 Type:Change ID:2610 Category:5 CategoryOld:6 Duration:433 • Tool displays 4 curves: • Whole history • Last period • Predicted resources • Reserved resources • Two calculation algorithms • Taking into account only number of players • Taking into account both number of players and behavior category

10. Conclusions and open issues Conclusions • Adapted the interaction complexities to specific action categories • Developed a load prediction tool • Confirmed significant discrepancies when calculating load just based on the number of players and based on behavioral information Open issues • Issues which cloud based MMORPGs face? • More “interaction” between shards • Is just adding another server when load hits certain treshold enough? • Load prediction based on spatial locality of the players + behavioral information