Adaptive scheduling server for power-aware real-time tasks

Mejía-Álvarez, Pedro; Levner, Eugene; Mossé, Daniel

doi:10.1145/993396.993400

Cited by 87 publications

(77 citation statements)

References 27 publications

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“…With the help of a DVS, f j can vary from f . From frequency, it is easy to obtain the speed of the CPU S j that is approximately proportional to the frequency of the machine [17], [26].…”

Section: A the System Modelmentioning

confidence: 99%

A goal programming approach for the joint optimization of energy consumption and response time in computational grids

Khan

2009

2009 IEEE 28th International Performance Computing and Communications Conference

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Abstract-We study the multi-objective problem of mapping independent tasks onto a set of computational grid machines that simultaneously minimizes the energy consumption and response time (makespan) subject to the constraints of deadlines and architectural requirements. We propose an algorithm based on goal programming that effectively converges to the compromised Pareto optimal solution. Compared to other traditional multi-objective optimization techniques that require identification of the Pareto frontier, goal programming directly converges to the compromised solution. Such a property makes goal programming a very efficient multi-objective optimization technique. Moreover, simulation results show that the proposed technique achieves superior performance compared to the greedy and linear relaxation heuristics, and competitive performance relative to the optimal solution implemented in LINDO for small-scale problems.

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“…With the help of a DVS, f j can vary from f . From frequency, it is easy to obtain the speed of the CPU S j that is approximately proportional to the frequency of the machine [17], [26].…”

Section: A the System Modelmentioning

confidence: 99%

A goal programming approach for the joint optimization of energy consumption and response time in computational grids

Khan

2009

2009 IEEE 28th International Performance Computing and Communications Conference

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“…For scheduling periodic real-time tasks on a variable speed processor with realistic discrete speeds, Mejia et al [25] have proposed a heuristic algorithm that finds near-optimal solutions at low cost. This method produces a 2-approximate solution to the optimization problem.…”

Section: Related Workmentioning

confidence: 99%

Energy Saving EDF Scheduling for Wireless Sensors on Variable Voltage Processors

Ghor¹,

Aggoune²

2014

IJACSA

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Abstract-Advances in micro technology has led to the development of miniaturized sensor nodes with wireless communication to perform several real-time computations. These systems are deployed wherever it is not possible to maintain a wired network infrastructure and to recharge/replace batteries and the goal is then to prolong as much as possible the lifetime of the system. In our work, we aim to modify the Earliest Deadline First (EDF) scheduling algorithm to minimize the energy consumption using the Dynamic Voltage and Frequency Selection. To this end, we propose an Energy Saving EDF (ES-EDF) algorithm that is capable of stretching the worst case execution time of tasks as much as possible without violating deadlines. We prove that ES-EDF is optimal in minimizing processor energy consumption and maximum lateness for which an upper bound on the processor energy saving is derived. In order to demonstrate the benefits of our algorithm, we evaluate it by means of simulation. Experimental results show that ES-EDF outperforms EDF and Enhanced EDF (E-EDF) algorithms in terms of both percentage of feasible task sets and energy savings.

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“…It is assumed that operating frequency of each machine is approximately proportionate to its processing speed (see [33]). The decrease in the supply voltage and frequency reduces the energy consumed by the machine.…”

Section: Energy Modelmentioning

confidence: 99%

Hierarchical genetic-based grid scheduling with energy optimization

et al. 2012

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An optimization of power and energy consumptions is the important concern for a design of modern-day and future computing and communication systems. Various techniques and high performance technologies have been investigated and developed for an efficient management of such systems. All these technologies should be able to provide good performance and to cope under an increased workload demand in the dynamic environments such as Computational Grids (CGs), clusters and clouds. In this paper we approach the independent batch scheduling in CG as a bi-objective minimization problem with makespan and energy consumption as the scheduling criteria. We use the Dynamic Voltage Scaling (DVS) methodology for scaling and possible reduction of cumulative power energy utilized by the system resources. We develop two implementations of Hierarchical Genetic Strategy-based grid scheduler (Green-HGS-Sched) with elitist and struggle replacement mechanisms. The proposed algorithms were empirically evaluated versus single-population Genetic Algorithms (GAs) and Island GA models for four CG size scenarios in static and dynamic modes. The simulation results show that proposed scheduling methodologies fairly reduce the energy usage and can be easily adapted to the dynamically changing grid states and various scheduling scenarios.

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Adaptive scheduling server for power-aware real-time tasks

Cited by 87 publications

References 27 publications

A goal programming approach for the joint optimization of energy consumption and response time in computational grids

A goal programming approach for the joint optimization of energy consumption and response time in computational grids

Energy Saving EDF Scheduling for Wireless Sensors on Variable Voltage Processors

Hierarchical genetic-based grid scheduling with energy optimization

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