Is Today’s Public Cloud Suited to Deploy Hardcore Realtime Services?

A CPU Perspective
  • Kjetil Raaen
  • Andreas Petlund
  • Pål Halvorsen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8374)


“Cloud computing” is a popular way for application providers to obtain a flexible server and network infrastructure. Providers deploying applications with tight response time requirements such as games, are reluctant to use clouds. An important reason is the lack of real-time guarantees. This paper evaluates the actual, practical soft real-time CPU performance of current cloud services, with a special focus on online games. To perform this evaluation, we created a small benchmark and calibrated it to take a few milliseconds to run (often referred to as a microbenchmrak). Repeating this benchmark at a high frequency gives an overview of available resources over time. From the experimental results, we find that public cloud services deliver performance mostly within the requirements of popular online games, where Microsoft Azure Virtual machines give a significantly more stable performance than Amazon EC2.


Cloud Computing Virtual Machine Cloud Service Online Game Public Cloud 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Amazon. Amazon EC2 Instance Types (2013),
  2. 2.
    Barker, S.K., Shenoy, P.: Empirical evaluation of latency-sensitive application performance in the cloud. In: Proceedings of ACM SIGMM on Multimedia Systems, MMSys 2010, pp. 35–46. ACM, New York (2010)Google Scholar
  3. 3.
    Chen, K.-T., Huang, P., Wang, G.-S., Huang, C.-Y., Lei, C.L.: On the Sensitivity of Online Game Playing Time to Network QoS. In: Proceedings of IEEE INFOCOM 2006(2006)Google Scholar
  4. 4.
    Claypool, M., Claypool, K.: Latency Can Kill: Precision and Deadline in Online Games. In: ACM Multimedia Systems Conference (2010)Google Scholar
  5. 5.
    El-Khamra, Y., Kim, H., Jha, S., Parashar, M.: Exploring the Performance Fluctuations of HPC Workloads on Clouds. In: 2010 IEEE Cloud Computing Technology and Science, pp. 383–387 (November 2010)Google Scholar
  6. 6.
    Microsoft. Microsoft Azure Pricing Details (2013),
  7. 7.
    Ostermann, S., Iosup, A., Yigitbasi, N., Prodan, R., Fahringer, T., Epema, D.: A performance analysis of EC2 cloud computing services for scientific computing. In: Ostermann, S., Iosup, A., Yigitbasi, N., Prodan, R., Fahringer, T., Epema, D. (eds.) Cloud Computing. LNICST, vol. 34, pp. 115–131. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  8. 8.
    Raaen, K., Espeland, H.: LEARS: A Lockless, Relaxed-Atomicity State Model for Parallel Execution of a Game Server Partition. In: Parallel Processing …, pp. 382–389. IEEE (September 2012)Google Scholar
  9. 9.
    Schad, J., Dittrich, J., Quiané-Ruiz, J.: Runtime measurements in the cloud: observing, analyzing, and reducing variance. Proceedings of the VLDB … 3(1) (2010)Google Scholar
  10. 10.
    Vaquero, L.M., Rodero-merino, L., Caceres, J., Lindner, M.: A Break in the Clouds: Towards a Cloud Definition. Computer Communication Review 39(1), 50–55 (2009)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Kjetil Raaen
    • 1
    • 2
    • 3
  • Andreas Petlund
    • 2
    • 3
  • Pål Halvorsen
    • 2
    • 3
  1. 1.NITHNorway
  2. 2.Simula Research LaboratoryNorway
  3. 3.Department of InformaticsUniversity of OsloNorway

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