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Enhancing the Data Centre Performance and QOS in Cloud Execution

Authors(4):

Yogesh M. Kotkar, Rahul D. Gaikwad, Nikhil D. Gangurde, Mangesh S. Mahajan
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In this, we will present the analytical model based on filtering the images that is scalable to model systems composed of thousands of the images and flexible to represent different policies and cloud specific strategies. Several performances filtering of images are defined and evaluated to analyse the behaviour of a cloud data centre, Utilization, Waiting Time, Ideal Time, Availability, Responsiveness and Scalability. Cloud data centre management is a key problem due to numerous and heterogeneous strategies that can be applied ranging from the cloud to other cloud. The performance evaluation of cloud computing infrastructure is required to predict the cost benefit of a strategy and the corresponding Quality of Service (QoS) experienced by users. A analysis is also provided to take into load balancing, finally a general approach will presented that starting from the concept of system capacity will help system managers to opportunely set of data centre parameter under different images filtering environment like grey scale, sepia etc.

Yogesh M. Kotkar, Rahul D. Gaikwad, Nikhil D. Gangurde, Mangesh S. Mahajan

Cloud Computing, Resilience, Responsiveness, Image Filtering Technique.

  1. Dario Bruneo, Member, IEEE “A Stochastic Model to Investigate Data Center Performance and QoS in IaaS Cloud Computing Systems,” VOL. 25, NO. 3, MARCH 2014.
  2. R. Buyya, R. Ranjan, and R. Calheiros, “Modeling and Simulation of Scalable Cloud Computing Environments and the Cloudsim Toolkit: Challenges and Opportunities,” Proc. Int’l Conf. High Performance Computing Simulation (HPCS ’09), pp. 1-11, June 2009.
  3. A. Iosup, N. Yigitbasi, and D. Epema, “On the Performance Variability of Production Cloud Services,” Proc. IEEE/ACM 11th Int’l Symp. Cluster, Cloud and Grid Computing (CCGrid), pp. 104-113, May 2011.
  4. V. Stantchev, “Performance Evaluation of Cloud Computing Offerings,” Proc. Third Int’l Conf. Advanced Eng. Computing and Applications in Sciences (ADVCOMP ’09), pp. 187-192, Oct. 2009.
  5. S. Ostermann et al., “Performance Analysis of Cloud Computing Services for Many-Tasks Scientific Computing,” Proc. Int’l Conf. Cloud Computing, LNCS vol. 22, pp. 1045-9219, Springer, Heidelberg, 2011.
  6. H. Khazaei, J. Misic, and V. Misic, “Performance Analysis of Cloud Computing Centers Using M/G/m/m+r Queuing Systems,” IEEE Trans. Parallel and Distributed Systems, vol. 23, no. 5, pp. 936-943, May 2012.
  7. R. Ghosh, K. Trivedi, V. Naik, and D.S. Kim, “End-to-End Performability Analysis for Infrastructure-as-a-Service Cloud: An Interacting Stochastic Models Approach,” Proc. IEEE 16th Pacific Rim Int’l Symp. Dependable Computing (PRDC), pp. 125-132, Dec. 2010.
  8. Noe Lopez-Benitez t, “Dependability Analysis of Distributed Computing Systems using Stochastic Petri Nets,” Department of Electrical Engineering Louisiana Tech University Ruston 1060-9857/ Aug. 1992.

Publication Details

Published in : Volume 1 | Issue 5 | September-October - 2015
Date of Publication Print ISSN Online ISSN
2015-10-25 2395-1990 2394-4099
Page(s) Manuscript Number   Publisher
187-191 IJSRSET151539   Technoscience Academy

Cite This Article

Yogesh M. Kotkar, Rahul D. Gaikwad, Nikhil D. Gangurde, Mangesh S. Mahajan, "Enhancing the Data Centre Performance and QOS in Cloud Execution", International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 1, Issue 5, pp.187-191, September-October-2015.
URL : http://ijsrset.com/IJSRSET151539.php