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Low-Complexity MPN Preemption Policy for Real-Time Task Scheduling

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Progress in Advanced Computing and Intelligent Engineering

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 714))

Abstract

Preemption plays a vital role in deciding and guaranteeing schedulability of real-time tasks. Over time, many preemption policies have been suggested in the literature ranging from no-preemption, full preemption, limited preemption, and recently a new MPN (mixed preemptive/non-preemptive) preemption policy. Optimal Algorithm (OA) given by Lee et al. for the disallowance of preemption can be further improved for low-time complexity at a little cost of reducing the number of schedulable task sets found. In this work, it is conjectured that if only a certain number of higher density tasks are selected for disallowance of preemption, then time complexity of Optimal Algorithm can be reduced substantially. Accordingly, a new Low-Complexity MPN (LCMPN) is proposed, implemented, and analyzed which has a lower time complexity than Optimal Algorithm. Simulated results of the proposed LCMPN in comparison to the Optimal Algorithm on the tested constrained task sets, justifies our conjecture.

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Author information

Authors and Affiliations

  1. Department of RIC, IKGPTU, Jalandhar, India

    Kiran Arora

  2. Department of CSE, BHSBIET, Lehragaga, India

    Kiran Arora

  3. Department of ECE, GZSCCET, Bathinda, India

    Savina Bansal & Rakesh Kumar Bansal

  4. MRSPTU, Bathinda, India

    Savina Bansal & Rakesh Kumar Bansal

Authors
  1. Kiran Arora
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  2. Savina Bansal
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  3. Rakesh Kumar Bansal
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Corresponding author

Correspondence to Kiran Arora .

Editor information

Editors and Affiliations

  1. Department of Computer Science, Rama Devi Women’s University, Bhubaneswar, Odisha, India

    Chhabi Rani Panigrahi

  2. Department of Computer Science, Central University of Rajasthan, Ajmer, Rajasthan, India

    Arun K. Pujari

  3. Department of Computer Science and Engineering, Indian Institute of Technology Kharagpur, Kharagpur, India

    Sudip Misra

  4. Department of Computer Science, Rama Devi Women’s University, Bhubaneswar, Odisha, India

    Bibudhendu Pati

  5. Department of Computer Science and Information Engineering (CSIE), Providence University, Taichung, Taiwan

    Kuan-Ching Li

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Arora, K., Bansal, S., Bansal, R.K. (2019). Low-Complexity MPN Preemption Policy for Real-Time Task Scheduling. In: Panigrahi, C., Pujari, A., Misra, S., Pati, B., Li, KC. (eds) Progress in Advanced Computing and Intelligent Engineering. Advances in Intelligent Systems and Computing, vol 714. Springer, Singapore. https://doi.org/10.1007/978-981-13-0224-4_49

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  • DOI: https://doi.org/10.1007/978-981-13-0224-4_49

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-0223-7

  • Online ISBN: 978-981-13-0224-4

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