skip to main content
research-article

Dynamic resource provisioning for cloud-based gaming infrastructures

Published:06 December 2012Publication History
Skip Abstract Section

Abstract

Modern massively multiplayer online games (MMOGs) allow hundreds of thousands of players to interact with a large, dynamic virtual world. Implementing a scalable MMOG service is challenging because the system is subject to high workload variability, but nevertheless must always operate under very strict quality of service (QoS) requirements. Traditionally, MMOG services are implemented as large dedicated IT infrastructures with aggressive over-provisioning of resources in order to cope with the worst-case workload scenario. In this article we address the problem of building a large-scale, multitier MMOG service using resources provided by a Cloud computing infrastructure. The Cloud paradigm allows customers to request as many resources as they need using a pay-as-you-go model. We harness this paradigm by proposing a dynamic provisioning algorithm, which can resize the resource pool of a MMOG service to adapt to workload variability and maintain a response time below a given threshold. We use a queuing network performance model to quickly estimate the system response time for different configurations. The performance model is used within a greedy algorithm to compute the minimum number of servers to be allocated on each tier in order to satisfy the system response time constraint. Numerical experiments are used to validate the effectiveness of the proposed approach.

References

  1. Balsamo, S. 2000. Product form queueing networks. In Performance Evaluation: Origins and Directions, G. Haring et al., Eds., LNCS 1769, Springer, Berlin, 377--401. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Baskett, F., Chandy, K. M., Muntz, R. R., and Palacios, F. G. 1975. Open, closed, and mixed networks of queues with different classes of customers. J. ACM 22, 2 (April), 248--260. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Cai, W., Xavier, P., Turner, S. J., and Lee, B.-S. 2002. A scalable architecture for supporting interactive games on the internet. In Proceedings of the 16th Workshop on Parallel and Distributed Simulation (PADS'02), IEEE, Washington, D.C., 60--67. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Chen, K.-T., Huang, P., and Lei, C.-L. 2006. How sensitive are online gamers to network quality? Commun. ACM 49, 34--38. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Dick, M., Wellnitz, O., and Wolf, L. C. 2005. Analysis of factors affecting players' performance and perception in multiplayer games. In Proceedings of the 4th Workshop on Network and System Support for Games (NETGAMES 2005), ACM, New York, 1--7. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Eaton, J. W. 2002. GNU Octave Manual. Network Theory Limited.Google ScholarGoogle Scholar
  7. Ferretti, S., Ghini, V., Panzieri, F., Pellegrini, M., and Turrini, E. 2010. QoS-aware Clouds. In Proceedings of the IEEE 3rd International Conference on Cloud Computing (CLOUD 2010), 321--328. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Gustafsson, F. 2000. Adaptive Filtering and Change Detection. John Wiley, Ltd.Google ScholarGoogle Scholar
  9. Hsiao, T.-Y. and Yuan, S.-M. 2005. Practical middleware for massively multiplayer online games. IEEE Internet Comput. 9, 47--54. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Jagex LTD. 2011. RuneScape. http://www.runescape.com/.Google ScholarGoogle Scholar
  11. Korn, A., Peltz, C., and Mowbray, M. 2009. A service level management authority in the cloud. Tech. rep. HPL-2009-79, HP Laboratories.Google ScholarGoogle Scholar
  12. Kumar, S., Chhugani, J., Kim, C., Kim, D., Nguyen, A., Dubey, P., Bienia, C., and Kim, Y. 2008. Second life and the new generation of virtual worlds. Computer 41, 9, 46--53. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Lazowska, E. D., Zahorjan, J., Graham, G. S., and Sevcik, K. C. 1984. Quantitative System Performance: Computer System Analysis Using Queueing Network Models. Prentice Hall, Englewood Cliffs, NJ. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Li, J., Chinneck, J., Woodside, M., Litoiu, M., and Iszlai, G. 2009. Performance model driven guarantees and optimization in Clouds. In Proceedings of the 2009 ICSE Workshop on Software Engineering Challenges of Cloud Computing (CLOUD'09), IEEE, Washington, D.C., 15--22. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Little, J. D. C. 1961. A proof for the queuing formula: L = λW. Oper. Res. 9, 3, 383--387.Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Marzolla, M. and Mirandola, R. 2010. Performanc-aware reconfiguration of software systems. In Proceedings of the Computer Performance Engineering, 7th European Performance Engineering Workshop (EPEW 2010), 23--24. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Mauve, M., Vogel, J., Hilt, V., and Effelsberg, W. 2004. Local-lag and timewarp: providing consistency for replicated continuous applications. IEEE Trans. Multimedia 6, 1, 47--57. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Meisner, L., Sadler, C. M., Barroso, L. A., Weber, W.-D.. and Wenisch, T. F. 2011. Power management of online data-intensive services. In Proceedings of the 38th Annual International Symposium on Computer Architecture (ISCA'11), ACM, New York, 319--330. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Nae, V., Iosup, A., and Prodan, R. 2010. Dynamic resource provisioning in massively multiplayer online games. IEEE Trans. Parallel Distrib. Syst. 99, 1--15. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Palazzi, C. E., Ferretti, S., Cacciaguerra, S., and Roccetti, M. 2006. Interactivity-loss avoidance in event delivery synchronization for mirrored game architectures. IEEE Trans. Multimedia 8, 4, 874--879. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Ranjan, S., Rolia, J., Fu, H., and Knightly, E. 2002. QoS-driven server migration for Internet data centers. In Proceedings of the Tenth IEEE International Workshop on Quality of Service, IEEE, Washington, D.C., 3--12.Google ScholarGoogle Scholar
  22. Reiser, M. and Lavenberg, S. S. 1980. Mean-value analysis of closed multichain queuing networks. J. ACM 27, 2, 313--322. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Spillner, J. and Schill, A. 2009. Dynamic SLA template adjustments based on service property monitoring. In Proceedings of the 2009 IEEE International Conference on Cloud Computing (CLOUD'09), IEEE, Washington, D.C., 183--189. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Urgaonkar, B., Pacifici, G., Shenoy, P., Spreitzer, M., and Tantawi, A. 2005. An analytical model for multi-tier internet services and its applications. SIGMETRICS Perform. Eval. Rev. 33, 1 (June), 291--302. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Urgaonkar, B., Shenoy, P., Chandra, A., Goyal, P., and Wood, T. 2008. Agile dynamic provisioning of multi-tier internet applications. ACM Trans. Auton. Adapt. Syst. 3, 1, 1--39. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. Zahorjan, J., Sevcik, K. C., Eager, D. L., and Galler, B. 1982. Balanced job bound analysis of queueing networks. Commun. ACM 25, 134--141. Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. Zhang, Q., Cheng, L., and Boutaba, R. 2010. Cloud computing: State-of-the-art and research challenges. J. Internet Services Appl. 1, 7--18.Google ScholarGoogle ScholarCross RefCross Ref

Index Terms

  1. Dynamic resource provisioning for cloud-based gaming infrastructures

              Recommendations

              Comments

              Login options

              Check if you have access through your login credentials or your institution to get full access on this article.

              Sign in

              Full Access

              • Published in

                cover image Computers in Entertainment
                Computers in Entertainment   Volume 10, Issue 1
                Theoretical and Practical Computer Applications in Entertainment
                October 2012
                103 pages
                EISSN:1544-3574
                DOI:10.1145/2381876
                Issue’s Table of Contents

                Copyright © 2012 ACM

                Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

                Publisher

                Association for Computing Machinery

                New York, NY, United States

                Publication History

                • Published: 6 December 2012
                • Revised: 1 July 2012
                • Accepted: 1 July 2012
                • Received: 1 May 2011

                Permissions

                Request permissions about this article.

                Request Permissions

                Check for updates

                Qualifiers

                • research-article
                • Research
                • Refereed

              PDF Format

              View or Download as a PDF file.

              PDF

              eReader

              View online with eReader.

              eReader

              HTML Format

              View this article in HTML Format .

              View HTML Format