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Scheduling Independent Partitions in Integrated Modular Avionics Systems

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  • Jinchao Chen
  • Chenglie Du
  • Pengcheng Han

Abstract

Recently the integrated modular avionics (IMA) architecture has been widely adopted by the avionics industry due to its strong partition mechanism. Although the IMA architecture can achieve effective cost reduction and reliability enhancement in the development of avionics systems, it results in a complex allocation and scheduling problem. All partitions in an IMA system should be integrated together according to a proper schedule such that their deadlines will be met even under the worst case situations. In order to help provide a proper scheduling table for all partitions in IMA systems, we study the schedulability of independent partitions on a multiprocessor platform in this paper. We firstly present an exact formulation to calculate the maximum scaling factor and determine whether all partitions are schedulable on a limited number of processors. Then with a Game Theory analogy, we design an approximation algorithm to solve the scheduling problem of partitions, by allowing each partition to optimize its own schedule according to the allocations of the others. Finally, simulation experiments are conducted to show the efficiency and reliability of the approach proposed in terms of time consumption and acceptance ratio.

Suggested Citation

  • Jinchao Chen & Chenglie Du & Pengcheng Han, 2016. "Scheduling Independent Partitions in Integrated Modular Avionics Systems," PLOS ONE, Public Library of Science, vol. 11(12), pages 1-18, December.
    • Handle: RePEc:plo:pone00:0168064
    DOI: 10.1371/journal.pone.0168064
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    References listed on IDEAS

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    1. Ali Hosseinabadi & Hajar Siar & Shahaboddin Shamshirband & Mohammad Shojafar & Mohd Nasir, 2015. "Using the gravitational emulation local search algorithm to solve the multi-objective flexible dynamic job shop scheduling problem in Small and Medium Enterprises," Annals of Operations Research, Springer, vol. 229(1), pages 451-474, June.
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