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Allocation algorithms for multicore partitioned mixed-criticality real-time systems.

Luis Ortiz1, Ana Guasque1, Patricia Balbastre1

  • 1Instituto de Automática e Informática Industrial (ai2), Universitat Politècnica de València, Valencia, Spain.

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Summary
This summary is machine-generated.

This study proposes a new hypervisor framework for mixed-criticality multicore systems. It efficiently allocates tasks to partitions and cores, reducing hypervisor overhead and ensuring feasible scheduling for critical applications.

Keywords:
AllocationMilpMixed criticalityPartitioned systemsReal-timeScheduling

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Area of Science:

  • Computer Engineering
  • Embedded Systems
  • Real-Time Systems

Background:

  • Multicore systems offer performance gains but require efficient resource allocation for critical applications.
  • Scheduling in multicore systems involves complex task and partition allocation, especially for mixed-criticality environments.
  • Existing methods face challenges in efficiently managing resources for critical partitioned multicore systems.

Purpose of the Study:

  • To propose a novel hypervisor partitioned framework for mixed-criticality systems.
  • To develop efficient methodologies for resource allocation and task scheduling in multicore partitioned systems.
  • To address the challenge of considering application criticality during system scheduling.

Main Methods:

  • A two-phase allocation process was implemented within a hypervisor partitioned framework.
  • Phase 1: Task-to-partition allocation using a Mixed-Integer Linear Programming (MILP) algorithm based on system criticality.
  • Phase 2: Task-to-core allocation using a second MILP algorithm and a modified worst fit decrease utilization approach.

Main Results:

  • Experimental results demonstrate the feasibility of the proposed scheduling strategy.
  • The combined allocation strategies led to a reduction in hypervisor overhead.
  • The framework effectively manages resource allocation for mixed-criticality partitioned multicore systems.

Conclusions:

  • The proposed hypervisor partitioned framework enables efficient and feasible scheduling for mixed-criticality multicore systems.
  • The two-phase allocation approach, combining MILP and a modified worst fit algorithm, successfully addresses scheduling complexities.
  • This methodology contributes to reducing overhead in critical embedded systems.