CPU scheduling for statistically-assured real-time performance and improved energy efficiency

We present a CPU scheduling algorithm, called Energy-efficient Utility Accrual Algorithm (or EUA), for battery-powered, embedded real-time systems. We consider an embedded software application model where repeatedly occurring application activities are subject to deadline constraints specified using...

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Vydáno v:CODES+ISSS 2004 : International Conference on Hardware/Software Codesign and System Synthesis : September 8-10, 2004, Stockholm, Sweden s. 110 - 115
Hlavní autoři: Wu, Haisang, Ravindran, Binoy, Jensen, E. Douglas, Li, Peng
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: New York, NY, USA ACM 08.09.2004
IEEE
Edice:ACM Conferences
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ISBN:1581139373, 9781581139372
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Abstract We present a CPU scheduling algorithm, called Energy-efficient Utility Accrual Algorithm (or EUA), for battery-powered, embedded real-time systems. We consider an embedded software application model where repeatedly occurring application activities are subject to deadline constraints specified using step time/utility functions. For battery-powered embedded systems, system-level energy consumption is also a primary concern. We consider CPU scheduling that (1) provides assurances on individual and collective application timeliness behaviors and (2) maximizes system-level timeliness and energy efficiency. Since the scheduling problem is intractable, EUA heuristically computes CPU schedules with a polynomial-time cost. Several properties of EUA are analytically established, including timeliness optimality during under-load situations and statistical assurances on timeliness behavior. Further, our simulation results confirm EUA's superior performance.
AbstractList We present a CPU scheduling algorithm, called Energy-efficient Utility Accrual Algorithm (or EUA), for battery-powered, embedded real-time systems. We consider an embedded software application model where repeatedly occurring application activities are subject to deadline constraints specified using step time/utility functions. For battery-powered embedded systems, system-level energy consumption is also a primary concern. We consider CPU scheduling that (1) provides assurances on individual and collective application timeliness behaviors and (2) maximizes system-level timeliness and energy efficiency. Since the scheduling problem is intractable, EUA heuristically computes CPU schedules with a polynomial-time cost. Several properties of EUA are analytically established, including timeliness optimality during under-load situations and statistical assurances on timeliness behavior. Further, our simulation results confirm EUA's superior performance.
Author Ravindran, Binoy
Li, Peng
Wu, Haisang
Jensen, E. Douglas
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  givenname: Peng
  surname: Li
  fullname: Li, Peng
  organization: Virginia Tech, Blacksburg, VA
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Keywords energy-efficient scheduling
real-time systems
time/utility functions
utility accrual scheduling
Language English
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Snippet We present a CPU scheduling algorithm, called Energy-efficient Utility Accrual Algorithm (or EUA), for battery-powered, embedded real-time systems. We consider...
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SubjectTerms Application software
Applied computing -- Computers in other domains
Computer systems organization -- Embedded and cyber-physical systems
Computer systems organization -- Embedded and cyber-physical systems -- Embedded systems
Computer systems organization -- Real-time systems
Costs
Embedded software
Embedded system
Energy consumption
Energy efficiency
Polynomials
Processor scheduling
Real time systems
Scheduling algorithm
Software and its engineering -- Software organization and properties -- Contextual software domains -- Operating systems -- Process management
Software and its engineering -- Software organization and properties -- Software system structures -- Embedded software
Software and its engineering -- Software organization and properties -- Software system structures -- Real-time systems software
Title CPU scheduling for statistically-assured real-time performance and improved energy efficiency
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