Study and Implementation of Resource Allocation Algorithms in Cloud Computing

  • Authors

    • Haitham Salman Chyad
    • Raniah Ali Mustafa
    • Kawther Thabt Saleh
    2018-11-30
    https://doi.org/10.14419/ijet.v7i4.28.25394
  • Cloud Computing, Cloud Performance Resource Optimization, Resource Scheduling

  • Abstract

    Now days, cloud based implementations are very prevalent and used widely for different types of services. At the point of deployment of cloud computing, there are enormous data centers and the associated virtual machines which work as per the scheduling and resource allocation approaches so that higher degree of optimization, accuracy and performance can be achieved from the cloud environment. The work presents the use of soft computing for the optimization and scheduling of the resources with the higher performance on cloud. This manuscript is having the key focus on the study and implementation of resource allocation and scheduling approaches in the cloud environment whereby there are enormous algorithms are integrated to escalate the overall performance of the cloud environment.

     

  • References

    1. [1] Mell, P. and Grance, T., 2011. The NIST definition of cloud computing.

      [2] Buyya, R., Yeo, C.S., Venugopal, S., Broberg, J. and Brandic, I., 2009. Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility. Future Generation computer systems, 25(6), pp.599-616.

      [3] Zhong, H., Tao, K. and Zhang, X., 2010, July. An approach to optimized resource scheduling algorithm for open-source cloud systems. In ChinaGrid Conference (ChinaGrid), 2010 Fifth Annual (pp. 124-129). IEEE.

      [4] Foster, I., Zhao, Y., Raicu, I. and Lu, S., 2008, November. Cloud computing and grid computing 360-degree compared. In Grid Computing Environments Workshop, 2008. GCE'08 (pp. 1-10). Ieee.

      [5] Saleem, M. and Rajouri, J.K., 2017. Cloud Computing Virtualization. International Journal of Computer Applications Technology and Research, 6(7), pp.290-292.

      [6] Jain, N., Payal, M. And Choudhary, M., 2018. Cloud Computing & Virtualization. Journal on Recent Innovation in Cloud Computing, Virtualization & Web Applications [ISSN: 2581-544X (online)], 2(1).

      [7] Beloglazov, A., Abawajy, J. and Buyya, R., 2012. Energy-aware resource allocation heuristics for efficient management of data centers for cloud computing. Future generation computer systems, 28(5), pp.755-768.

      [8] Zhang, Q., Cheng, L. and Boutaba, R., 2010. Cloud computing: state-of-the-art and research challenges. Journal of internet services and applications, 1(1), pp.7-18.

      [9] Li, B., Li, J., Huai, J., Wo, T., Li, Q. and Zhong, L., 2009, September. Enacloud: An energy-saving application live placement approach for cloud computing environments. In 2009 IEEE International Conference on Cloud Computing (pp. 17-24). IEEE.

      [10] Hu, J., Gu, J., Sun, G. and Zhao, T., 2010, December. A scheduling strategy on load balancing of virtual machine resources in cloud computing environment. In Parallel Architectures, Algorithms and Programming (PAAP), 2010 Third International Symposium on (pp. 89-96). IEEE.

  • Downloads

  • How to Cite

    Salman Chyad, H., Ali Mustafa, R., & Thabt Saleh, K. (2018). Study and Implementation of Resource Allocation Algorithms in Cloud Computing. International Journal of Engineering & Technology, 7(4.28), 591-594. https://doi.org/10.14419/ijet.v7i4.28.25394

    Received date: 2019-01-04

    Accepted date: 2019-01-04

    Published date: 2018-11-30