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Fast Handling of Cloud Data Based on user Level Virtualization and Resource Scheduling

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  • P. Aron Bami
  • M. Velladurai

Abstract

Many believe the future of gaming lies in the cloud, namely Cloud Gaming, which renders an interactive gaming application in the cloud and streams the scenes as a video sequence to the player over Internet. This paper proposes GCloud, a GPU/CPU hybrid cluster for cloud gaming based on the user-level virtualization technology. Specially, we present a performance model to analyze the server-capacity and games resource-consumptions, which categorizes games into two types: CPU-critical and memory-io-critical. Consequently, several scheduling strategies have been proposed to improve the resource-utilization and compared with others. Simulation tests show that both of the First-Fit-like and the Best-Fit-like strategies outperform the other(s); especially they are near optimal in the batch processing mode. Other test results indicate that GCloud is efficient: An off-the-shelf PC can support five high-end video-games run at the same time. In addition, the average per-frame processing delay is 8_19 ms under different image-resolutions, which outperforms other similar solutions.

Suggested Citation

  • P. Aron Bami & M. Velladurai, 2017. "Fast Handling of Cloud Data Based on user Level Virtualization and Resource Scheduling," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 2(2), pages 69-74, April.
    • Handle: RePEc:jbh:ijsrcs:v2:y2017:i2:id:hcseit17225
    Note: Article URL: https://ijsrcseit.com/CSEIT17225
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