1. 1 Google Workshop at TU Delft, 2010 – Online Games and Clouds Cloudifying Games: Rain for the Thirsty Alexandru Iosup Parallel and Distributed Systems Group Delft University of Technology Our team: Undergrad Adrian Lascateu, Alexandru Dimitriu (UPB, Romania), …, Grad Vlad Nae (U. Innsbruck, Austria), Siqi Shen (TU Delft, the Netherlands), … Staff Dick Epema, Henk Sips (TU Delft), Thomas Fahringer, Radu Prodan (U. Innsbruck), Nicolae Tapus, Mihaela Balint, Vlad Posea (UPB), etc.

2. Google Workshop at TU Delft, 2010 – Online Games and Clouds 2 What’s in a name? MSG, MMOG, MMO, … 1.Virtual world Explore, do, learn, socialize, compete + 2.Content Graphics, maps, puzzles, quests, culture + 3.Game data Player stats and relationships Romeo and Juliet Massively Social Gaming = (online) games with massive numbers of players (100K+), for which social interaction helps the gaming experience 250,000,000 active players

3. Google Workshop at TU Delft, 2010 – Online Games and Clouds 3 Cloud Futures Workshop 2010 – Cloud Computing Support for Massively Social Gaming 3 Background on Cloud Computing “The path to abundance” On-demand capacity Pay what you use Great for web apps (EIP, web crawl, DB ops, I/O) “The killer cyclone” Not so great performance for compute- or data- intensive applications 1 Long-term perf. variability 2 http://www.flickr.com/photos/dimitrisotiropoulos/4204766418/ Tropical Cyclone Nargis (NASA, ISSS, 04/29/08) 1- Iosup et al., Performance Analysis of Cloud Computing Services for Many Tasks Scientific Computing, IEEE TPDS, 2011. 2- Iosup et al., On the Performance Variability of Production Cloud Services, CCGrid 2011. VS

4. Google Workshop at TU Delft, 2010 – Online Games and Clouds 4 Cloudifying: PaaS for MSGs (Platform Challenge) Build MSG platform that uses (mostly) cloud resources Close to players No upfront costs, no maintenance Compute platforms: multi-cores, GPUs, clusters, all-in-one! Performance guarantees Code for various compute platforms—platform profiling Misprediction=$$$ What services? Vendor lock-in? My data Nae, Iosup, Prodan, Dynamic Resource Provisioning in Massively Multiplayer Online Games, IEEE TPDS, 2011.

5. Google Workshop at TU Delft, 2010 – Online Games and Clouds 5 Cloudifying: Content, Content, Content (Content Challenge) Produce and distribute content for 1BN people Game Analytics  Game statistic Crowdsourcing Storification Auto-generated game content Adaptive game content Content distribution/ Streaming content A. Iosup, POGGI: Puzzle-Based Online Games on Grid Infrastructures, EuroPar 2009 (Best Paper Award)

6. Google Workshop at TU Delft, 2010 – Online Games and Clouds 6 Cloudifying: Social Everything! Social Network=undirected graph, relationship=edge Community=sub-graph, density of edges between its nodes higher than density of edges outside sub-graph (Analytics Challenge) Build cloud-based layer to Improve gaming experience Ranking / Rating Matchmaking / Recommendations Play Style/Tutoring Organize Gaming Communities Player Behavior A. Iosup, CAMEO: Continuous Analytics for Massively Multiplayer Online Games on Cloud Resources. ROIA, Euro-Par 2009 Workshops.

7. Google Workshop at TU Delft, 2010 – Online Games and Clouds 7 Summary Current Technology The Future Happy players Happy cloud operators Million-user, multi-bn market Sim, Content, Analytics Massive Social Gaming Upfront payment Cost and scalability problems Makes players unhappy Our Vision Scalability & Automation Economy of scale with clouds Ongoing Work Content: POGGI Framework Platform: edutain@grid Analytics: CAMEO Framework Publications Gaming and Clouds 2008: ACM SC 2009: ROIA, CCGrid, NetGames, EuroPar (Best Paper Award), … 2010: IEEE TPDS, Elsevier CCPE,… 2011: Book Chapter, IEEE TPDS, IJAMC, … Graduation (Forecast) 2011-2014: 3PhD, 10+MSc, nBSc

8. Google Workshop at TU Delft, 2010 – Online Games and Clouds 8 Thank you for your attention! Questions? Suggestions? Observations? Alexandru Iosup A.Iosup@tudelft.nl http://www.pds.ewi.tudelft.nl/~iosup/ (or google “iosup”) Parallel and Distributed Systems Group Delft University of Technology A.Iosup@tudelft.nl http://www.pds.ewi.tudelft.nl/~iosup/ - http://www.st.ewi.tudelft.nl/~iosup/research.htmlhttp://www.st.ewi.tudelft.nl/~iosup/research.html - http://www.st.ewi.tudelft.nl/~iosup/research_gaming.htmlhttp://www.st.ewi.tudelft.nl/~iosup/research_gaming.html - http://www.st.ewi.tudelft.nl/~iosup/research_cloud.htmlhttp://www.st.ewi.tudelft.nl/~iosup/research_cloud.html More Info: Do not hesitate to contact me…

9. Google Workshop at TU Delft, 2010 – Online Games and Clouds 9

10. 10 Cloud Computing [1/2] Low Performance for Sci.Comp. Evaluated the performance of resources from four production, commercial clouds. GrenchMark for evaluating the performance of cloud resources Four production, commercial IaaS clouds: Amazon Elastic Compute Cloud (EC2), Mosso, Elastic Hosts, and GoGrid. Finding: cloud performance low for sci.comp. S. Ostermann, A. Iosup, N. Yigitbasi, R. Prodan, T. Fahringer, and D. Epema, A Performance Analysis of EC2 Cloud Computing Services for Scientific Computing, Cloudcomp 2009, LNICST 34, pp. 115–131, 2010. N. Yigitbasi, A. Iosup, D. Epema, S. Ostermann: C-Meter: A Framework for Performance Analysis of Computing Clouds. Proc. of CCGRID 2009: 472-477

11. Google Workshop at TU Delft, 2010 – Online Games and Clouds 11 Cloud Computing [2/2] Cloud Performance Variability Performance variability of production cloud services IaaS: Amazon Web Services PaaS: Google App Engine Year-long performance information for nine services Finding: about half of the cloud services investigated in this work exhibits yearly and daily patterns; impact of performance variability depends on application. A. Iosup, N. Yigitbasi, and D. Epema, On the Performance Variability of Production Cloud Services, CCGrid 2011. Amazon S3: GET US HI operations