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Scheduling for energy and reliability management on multiprocessor real-time systems.

机译:在多处理器实时系统上安排能源和可靠性管理。

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摘要

Scheduling algorithms for multiprocessor real-time systems have been studied for years with many well-recognized algorithms proposed. However, it is still an evolving research area and many problems remain open due to their intrinsic complexities. With the emergence of multicore processors, it is necessary to re-investigate the scheduling problems and design/develop efficient algorithms for better system utilization, low scheduling overhead, high energy efficiency, and better system reliability. Focusing cluster schedulings with optimal global schedulers, we study the utilization bound and scheduling overhead for a class of cluster-optimal schedulers. Then, taking energy/power consumption into consideration, we developed energy-efficient scheduling algorithms for real-time systems, especially for the proliferating embedded systems with limited energy budget. As the commonly deployed energy-saving technique (e.g. dynamic voltage frequency scaling (DVFS)) will significantly affect system reliability, we study schedulers that have intelligent mechanisms to recuperate system reliability to satisfy the quality assurance requirements. Extensive simulation is conducted to evaluate the performance of the proposed algorithms on reduction of scheduling overhead, energy saving, and reliability improvement. The simulation results show that the proposed reliability-aware power management schemes could preserve the system reliability while still achieving substantial energy saving.
机译:对于多处理器实时系统的调度算法,已经进行了多年研究,并提出了许多公认的算法。但是,它仍然是一个不断发展的研究领域,由于其内在的复杂性,许多问题仍然存在。随着多核处理器的出现,有必要重新研究调度问题并设计/开发有效的算法,以提高系统利用率,降低调度开销,提高能效并提高系统可靠性。重点关注具有最佳全局调度程序的群集调度,我们研究了一类群集最佳调度程序的利用率限制和调度开销。然后,考虑到能源/功耗,我们为实时系统开发了节能调度算法,尤其是对于能源预算有限的激增嵌入式系统。由于通常采用的节能技术(例如动态电压频率缩放(DVFS))将显着影响系统可靠性,因此我们研究了具有智能机制以恢复系统可靠性以满足质量保证要求的调度程序。进行了广泛的仿真,以评估所提出算法在减少调度开销,节省能源和提高可靠性方面的性能。仿真结果表明,所提出的具有可靠性的电源管理方案可以在保持系统可靠性的同时,还可以节省大量能源。

著录项

  • 作者

    Qi, Xuan.;

  • 作者单位

    The University of Texas at San Antonio.;

  • 授予单位 The University of Texas at San Antonio.;
  • 学科 Energy.;Computer Science.
  • 学位 Ph.D.
  • 年度 2011
  • 页码 112 p.
  • 总页数 112
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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