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Cameo: Continuous analytics for massively multiplayer online games (2009)
| Venue: | In ROIA 2009, LNCS |
| Citations: | 4 - 2 self |
BibTeX
@INPROCEEDINGS{Iosup09cameo:continuous,
author = {Alexandru Iosup},
title = {Cameo: Continuous analytics for massively multiplayer online games},
booktitle = {In ROIA 2009, LNCS},
year = {2009},
pages = {1--10},
publisher = {Springer}
}
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Abstract
Abstract. Massively Multiplayer Online Games (MMOGs) have grown to entertain tens of millions of players daily. Currently, the game operators and third-parties using gameplay information rely on pre-provisioned resources to analyze the current status of the player community and the evolution of this status over time. Instead, with the appearance of cloud computing it has become attractive to use on-demand resources to run automated MMOG data analytics tools. Thus, in this work we introduce CAMEO, an architecture for Continuous Analytics for Massively multiplayEr Online games on cloud resources. Our architecture provides various mechanisms for MMOG data collection and continuous analytics of a pre-determined accuracy in real settings. We assess the capabilities of our approach by taking and analyzing complete or partial snapshots from Runescape, one of the most popular MMOGs with a community of over 3,000,000 active players. Notably, we show evidence that CAMEO already supports simple continuous MMOG analytics, and give a first estimation of the costs of the analytic process. 1
Keyphrases
continuous analytics multiplayer online game popular mmogs first estimation various mechanism partial snapshot cloud resource gameplay information player community online game game operator analytic process current status mmog data analytics tool pre-provisioned resource mmog data collection on-demand resource massively multiplayer online game active player pre-determined accuracy simple continuous mmog analytics real setting
