Open Access Journal

ISSN : 2394-2320 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

Call For Paper : Vol 11, Issue 03, March 2024

Call for Paper

Vol 11, Issue 03, March 2024

Indexing

VM Auto-Scaling for Cloud Computing

Author : Dr. M Sivaram 1

PDF

Date of Publication :23rd March 2017

Abstract: Appearance of Science Clouds empowers researchers to encourage enormous scale logical computational examinations over cloud condition. Many undertaking figuring (MTC) in computational science needs to testament stable executions of applications even in quick changes of crucial status of physical assets and supports superior assets in a long enough said. Auto-scaling approach on virtual machines (VM) increments effective cloud assets the board for the computational critical thinking condition. Different auto scaling techniques which give valuable asset the executives by and by are being discussed and examined. In any case, the majority of the auto-scaling strategies are simply effectively considered in execution measurements or execution cut-off time in explicit outstanding tasks at hand yet not in different examples of work process. We propose an auto-scaling technique, ensuring the execution of different examples of work process inside cut-off time in cross breed cloud condition. The test results show the technique works powerfully also, acceptably on half and half cloud assets for different work process designs having arbitrary remaining burden reliance

Reference :

    1. A. F. Antonescu and T. Braun, “Simulation of SLA-based VM-scaling algorithms for clouddistributed applications,” Futur. Gener. Comput. Syst., 2016, doi: 10.1016/j.future.2015.01.015.
    2. C. W. Huang, W. H. Hu, C. C. Shih, B. T. Lin, and C. W. Cheng, “The improvement of autoscaling mechanism for distributed database - A case study for MongoDB,” in 15th Asia-Pacific Network Operations and Management Symposium: “Integrated Management of Network Virtualization”, APNOMS 2013, 2013.
    3. J. Jiang, J. Lu, G. Zhang, and G. Long, “Optimal cloud resource auto-scaling for web applications,” in Proceedings - 13th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, CCGrid 2013, 2013, doi: 10.1109/CCGrid.2013.73.
    4. R. Han, L. Guo, M. M. Ghanem, and Y. Guo, “Lightweight resource scaling for cloud applications,” in Proceedings - 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGrid 2012, 2012, doi: 10.1109/CCGrid.2012.52.
    5. K. Krampis et al., “Cloud BioLinux: Preconfigured and on-demand bioinformatics computing for the genomics community,” BMC Bioinformatics, 2012, doi: 10.1186/1471-2105- 13-42.
    6. L. Popa, G. Kumar, M. Chowdhury, A. Krishnamurthy, S. Ratnasamy, and I. Stoica, “FairCloud: Sharing the network in cloud computing,” in Computer Communication Review, 2012, doi: 10.1145/2377677.2377717
    7. T. Lorido-Botran, J. Miguel-Alonso, and J. A. Lozano, “A Review of Auto-scaling Techniques for Elastic Applications in Cloud Environments,” J. Grid Comput., 2014, doi: 10.1007/s10723-014-9314-7.
    8. E. Caron, F. Desprez, and A. Muresan, “Pattern Matching Based Forecast of Non-periodic Repetitive Behavior for Cloud Clients,” J. Grid Comput., 2011, doi: 10.1007/s10723-010-9178- 4.
    9. A. Pérez, G. Moltó, M. Caballer, and A. Calatrava, “Serverless computing for containerbased architectures,” Futur. Gener. Comput. Syst., 2018, doi: 10.1016/j.future.2018.01.022.
    10. M. Satyanarayanan, P. Bahl, R. Cáceres, and N. Davies, “The case for VM-based cloudlets in mobile computing,” IEEE Pervasive Comput., 2009, doi: 10.1109/MPRV.2009.82.
    11. M. Mao and M. Humphrey, “Auto-scaling to minimize cost and meet application deadlines in cloud workflows,” in Proceedings of 2011 SC - International Conference for High Performance Computing, Networking, Storage and Analysis, 2011, doi: 10.1145/2063384.2063449.
    12. T. Ristenpart, E. Tromer, H. Shacham, and S. Savage, “Hey, you, get off of my cloud: Exploring information leakage in third-party compute clouds,” in Proceedings of the ACM Conference on Computer and Communications Security, 2009, doi: 10.1145/1653662.1653687.
    13. B. Dougherty, J. White, and D. C. Schmidt, “Model-driven auto-scaling of green cloud computing infrastructure,” Futur. Gener. Comput. Syst., 2012, doi: 10.1016/j.future.2011.05.009.
    14. S Balamurugan, RP Shermy, Gokul Kruba Shanker, VS Kumar, VM Prabhakaran, “An Object Oriented Perspective of Context–Aware Monitoring Strategies for Cloud based Healthcare Systems”,Asian Journal of Research in Social Sciences and Humanities, Volume : 6, Issue : 8, 2016
    15. S Balamurugan, P Anushree, S Adhiyaman, Gokul Kruba Shanker, VS Kumar, “RAIN Computing: Reliable and Adaptable Iot Network (RAIN) Computing”, Asian Journal of Research in Social Sciences and Humanities, Volume : 6, Issue : 8, 2016
    16. Usha Yadav, Gagandeep Singh Narula, Neelam Duhan, Vishal Jain, “Ontology Engineering and Development Aspects: A Survey”, International Journal of Education and Management Engineering (IJEME), Hongkong, Vol. 6, No. 3, May 2016, page no. 9 – 19 having ISSN No. 2305-3623.
    17. Vishal Assija, Anupam Baliyan and Vishal Jain, “Effective & Efficient Digital Advertisement Algorithms”, CSI-2015; 50th Golden Jubilee Annual Convention on “Digital Life”, held on 02nd to 05th December, 2015 at New Delhi, published by the Springer under ICT Based Innovations, Advances in Intelligent Systems and Computing having ISBN 978-981-10-6602- 3 from page no. 83 to 91.
    18. Vishal Jain and Dr. S. V. A. V. Prasad, “Analysis of RDBMS and Semantic Web Search in University System”, International Journal of Engineering Sciences & Emerging Technologies (IJESET), Volume 7, Issue 2, October 2014, page no. 604-621 having ISSN No. 2231-6604.

Recent Article