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University of Zagreb MMVE 2012 workshop1 Towards Reinterpretation of Interaction Complexity for Load Prediction in Cloud-based MMORPGs Mirko Sužnjević, Maja Matijašević University of Zagreb Faculty of Electrical Engineering and Computing Department of Telecommunications http://www.fer.unizg.hr/ztel/en/research/research_groups/netmedia
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2 University of Zagreb MMVE 2012 workshop Motivation 10 September 2015 Number of players on a server = 4000 Not the same in terms of load!
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3 University of Zagreb MMVE 2012 workshop Outline Introduction Related work Mapping Load prediction Resuts Conclusion and open issues 10 September 2015
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4 University of Zagreb MMVE 2012 workshop 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 10 September 2015
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5 University of Zagreb MMVE 2012 workshop 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. 10 September 2015
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6 University of Zagreb MMVE 2012 workshop 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 10 September 2015
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7 University of Zagreb MMVE 2012 workshop 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 10 September 2015
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8 University of Zagreb MMVE 2012 workshop Load prediction II 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 10 September 2015 Second:124164 Type:Change ID:2610 Category:5 CategoryOld:6 Duration:433
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9 University of Zagreb MMVE 2012 workshop Results 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 September 2015 Second:124164 Type:Change ID:2610 Category:5 CategoryOld:6 Duration:433
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10 University of Zagreb MMVE 2012 workshop 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 10 September 2015
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University of Zagreb MMVE 2012 workshop11 10 September 2015
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