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Prediction of Service-Level Agreement Violation in Cloud Computing Using Bayesian Regularisation

  • Archana Pandita
  • Prabhat Kumar UpadhyayEmail author
  • Nisheeth Joshi
Conference paper
  • 62 Downloads
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1141)

Abstract

service-level agreement (sla) is a contract between the cloud service provider and consumer which includes terms and conditions of service parameters. the cloud service provider has to commit to service-level agreements, which ensures a specific quality of performance. a certain level of penalty is set if the provider performs sla violations. managing and applying penalties has become a critical issue for cloud computing. it is found to be of paramount importance that the violations are predicted well in advance so that the necessary measures can be taken. in this research work, various proactive sla prediction models were designed, utilising the power of machine learning. we have used real-world data sets to highlight the accurate models for violation prediction in a cloud environment. seeing violation prediction as a classification problem where incoming requests need to be predicted for the violation, we have used bayesian regularised artificial neural network (brann) on different samples of real-world data set. both the models show remarkable performance for predicting sla violation. brann shows a significantly good average accuracy of 97.6%.

Keywords

Bayesian regularised artificial neural network Cloud computing Neural network Prediction SLA violation 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2021

Authors and Affiliations

  • Archana Pandita
    • 1
  • Prabhat Kumar Upadhyay
    • 2
    Email author
  • Nisheeth Joshi
    • 3
  1. 1.Dept. of CSEBirla Institute of Technology Offshore CampusRas al KhaimahUAE
  2. 2.Department of EEEBirla Institute of Technology, MesraRanchiIndia
  3. 3.Department of CSEBanasthali UniversityVanasthaliIndia

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