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Designing Parallel Operation for High-Performance Cloud Computing Using Partition Algorithm

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Intelligence in Big Data Technologies—Beyond the Hype

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1167))

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Abstract

Cloud computing comes up with the efficiency of storing an enormous amount of data to retrieve and to maintain. It has a huge amount of advantages for platforms such as Amazon, Google, and Microsoft. Some best advantages are maintaining quality, cost reduction, preventing the loss, extendibility. With all these, the performance of cloud computing assumes a significant job in every stage of the cloud. The expectation of platform viewers and owners need the performance of the cloud should be skyscraping. But achieving the high performance of cloud computing is a big deal in reality. The performance of cloud computing can analyze based on the environment which is used. The high-performance cloud computing (HPCC) is defined as a sort of distributed computing arrangement that fuses principles, systems, and components from distributed computing. The total arrangement may incorporate capacity, equipment, and application programming, which will all be conveyed through the cloud on an on interest premise. So, in this paper, we had briefly explained cloud models and services. The main discussion that is carried out here is the difference between CC and HPCC. The partition algorithm is used for designing parallel operation for HPCC to lift in selection at the expense of supply and to reduce the performance time of taking input operations (or) conditions.

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Author information

Authors and Affiliations

  1. Department of Information Technology, PSNA College of Engineering and Technology, Dindigul, India

    Krishnan Rajkumar & A. Sangeetha

  2. Department of Computer Science and Engineering, Karunya Institute of Technology and Sciences, Coimbatore, India

    V. Ebenezer & N. Karthik

  3. Department of Information TechnologyComp, KLN College of Engineering and Technology, Madurai, India

    G. Ramesh

Authors
  1. Krishnan Rajkumar
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  2. A. Sangeetha
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  3. V. Ebenezer
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  4. G. Ramesh
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  5. N. Karthik
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Corresponding author

Correspondence to Krishnan Rajkumar .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Karunya Institute of Technology and Sciences, Coimbatore, Tamil Nadu, India

    J. Dinesh Peter

  2. Department of Computer Science, University of Central Florida, Orlando, FL, USA

    Steven L. Fernandes

  3. Department of Civil and Environmental Engineering, University of Pittsburgh, Pittsburgh, PA, USA

    Amir H. Alavi

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Rajkumar, K., Sangeetha, A., Ebenezer, V., Ramesh, G., Karthik, N. (2021). Designing Parallel Operation for High-Performance Cloud Computing Using Partition Algorithm. In: Peter, J., Fernandes, S., Alavi, A. (eds) Intelligence in Big Data Technologies—Beyond the Hype. Advances in Intelligent Systems and Computing, vol 1167. Springer, Singapore. https://doi.org/10.1007/978-981-15-5285-4_45

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