Data caching issues in an information retrieval system
ACM Transactions on Database Systems (TODS)
ACM Transactions on Internet Technology (TOIT)
Proceedings of the 11th international conference on World Wide Web
A Survey of Methods for Scaling Up Inductive Algorithms
Data Mining and Knowledge Discovery
Efficient Numerical Error Bounding for Replicated Network Services
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Presence: Teleoperators and Virtual Environments - Special issue: Virtual heritage
Scaling up all pairs similarity search
Proceedings of the 16th international conference on World Wide Web
IRLbot: scaling to 6 billion pages and beyond
Proceedings of the 17th international conference on World Wide Web
Amazon S3 for science grids: a viable solution?
DADC '08 Proceedings of the 2008 international workshop on Data-aware distributed computing
Inter-operating grids through Delegated MatchMaking
Scientific Programming - Large-Scale Programming Tools and Environments
Efficient management of data center resources for massively multiplayer online games
Proceedings of the 2008 ACM/IEEE conference on Supercomputing
POGGI: Puzzle-Based Online Games on Grid Infrastructures
Euro-Par '09 Proceedings of the 15th International Euro-Par Conference on Parallel Processing
Proceedings of the 9th Annual Workshop on Network and Systems Support for Games
The Cloud: Requirements for a Better Service
CCGRID '12 Proceedings of the 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012)
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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 preprovisioned 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.