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SLA-Based Group Tasks Max-Min (GTMax-Min) Algorithm for Task Scheduling in Multi-Cloud Environments

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Operationalizing Multi-Cloud Environments

Part of the book series: EAI/Springer Innovations in Communication and Computing ((EAISICC))

Abstract

Cloud is a distributed heterogeneous computing paradigm that facilitates on-demand delivery of IT heterogeneous resources to the customer based on their needs over the Internet with a pay-as-per service they use. Service level agreement (SLA) specifies the customer’s expected service levels through cloud service provider (CSP) and the remedies or penalties if any of the CSP does not meet agreed-on service levels. Before providing the requested services to the customer, CSP and customer negotiate and sign on an SLA. CSP earns money for the service provided to the customer on satisfying the agreed-on service levels. Otherwise, CSP pays the penalty cost to the customer for the violation of SLA. Task scheduling minimizes task execution time and maximizes resource usage rate. Scheduling objective tends to improve quality of service (QoS) parameters like resource usage, with a minimum execution time and cost (without violating SLA). The proposed algorithm SLA-GTMax-Min schedules the tasks efficiently to the heterogeneous multi-cloud environment satisfying SLA and balances makespan, gain, and penalty/violation cost. Proposed SLA-GTMax-Min represents three levels of SLA provided with three types of services expected by the customers. The services are namely tasks minimum execution time, tasks minimum gain cost, and tasks both minimum execution time and gain cost in percentage, respectively. Makespan is termed as tasks minimum execution time. Gain cost represents minimum execution cost for completing tasks execution. The proposed algorithm SLA-GTMax-Min incorporates the SLA gain cost for providing service successfully and SLA violation cost for providing service unsuccessfully. Performance analysis of algorithm SLA-GTMax-Min and existing algorithm is measured based on the benchmark dataset values. The experimental results of SLA-GTMax-Min algorithm and the existing scheduling algorithms, namely, SLA-MCT, Execution-MCT, Profit-MCT, SLA-Min-Min, Execution-Min-Min, and Profit-Min-Min, are compared by evaluation metrics. Evaluation measure considered for evaluating the performance of the proposed SLA-GTMax-Min algorithm are makespan, cloud utilization ratio, gain cost is the cost earned by the CSP for successful completion of the tasks, and penalty cost the CSP pays to the customer for violation of SLA. The experimental results illustrate clearly algorithm SLA-GTMax-Min performs a better balance among makespan, gain cost, and penalty cost than existing algorithms.

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Authors and Affiliations

  1. Department of Information Technology, Kongu Engineering College, Perundurai, India

    G. K. Kamalam & K. Sentamilselvan

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  1. G. K. Kamalam
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  2. K. Sentamilselvan
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Editors and Affiliations

  1. Sri Venkateswara College of Engineering, Sriperumbudur, India

    Rajganesh Nagarajan

  2. Reliance Jio Infocomm. Ltd., RJIL, Bangalore, India

    Pethuru Raj

  3. Vellore Institute of Technology, Vellore, India

    Ramkumar Thirunavukarasu

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Kamalam, G.K., Sentamilselvan, K. (2022). SLA-Based Group Tasks Max-Min (GTMax-Min) Algorithm for Task Scheduling in Multi-Cloud Environments. In: Nagarajan, R., Raj, P., Thirunavukarasu, R. (eds) Operationalizing Multi-Cloud Environments. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-74402-1_6

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  • DOI: https://doi.org/10.1007/978-3-030-74402-1_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-74401-4

  • Online ISBN: 978-3-030-74402-1

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