Energy-efficient deadline scheduling for heterogeneous systems

Ma, Yan; Gong, Bin; Sugihara, Ryo; Gupta, Rajesh K.

doi:10.1016/j.jpdc.2012.07.006

Cited by 45 publications

(12 citation statements)

References 48 publications

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“…The size of random task graph was varied by considering the different number of tasks as 20 (small size), 40, 60 (medium size), 80 and 100 (large size) to represent the different size parallel application (as taken in [50][51][52]). The computation cost of each task t i on resource r j is selected randomly by the uniform distribution with the mean being equal to twice the specified average computation cost (set as 20).…”

Section: Simulation Results and Analysismentioning

confidence: 99%

Energy-Aware Workflow Scheduling in Grid Under QoS Constraints

Garg

Singh

2015

Arab J Sci Eng

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In this study, we have considered the problem of scheduling precedence-constraint parallel applications (workflows) in heterogeneous grid-computing environment. Recently many heuristics have been devoted to grid scheduling typically restricted to optimizing the execution time (makespan) only without paying much concentration on energy consumption. Reducing energy consumption can bring various advantages like reducing operating costs, environmental perspective and increase in system reliability. This paper aims to develop energy-aware task scheduling algorithm in grid based on the dynamic voltage and frequency scaling (DVFS) technique. The user negotiates with the service provider on their quality of service (QoS) requirements along with green computing specifications to reach the service level agreement. With the use of DVFS, the algorithm minimizes the energy consumption of task execution while satisfying the QoS constraints (deadline). The proposed static scheduling algorithm works in three phases: deadline distribution, tasks ordering and then assigning the best services to tasks along with selecting the appropriate voltage levels while meeting its sub-deadline. The simulation results using randomly generated task graphs and task graphs corresponding to real-world problems exhibit that the proposed algorithm achieves energy efficiency and reduces energy consumption up to 68 % with the increase in 30 % of the execution time.B Ritu Garg

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Section: Simulation Results and Analysismentioning

confidence: 99%

Energy-Aware Workflow Scheduling in Grid Under QoS Constraints

Garg

Singh

2015

Arab J Sci Eng

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“…Goiri et al [5] presented a dynamic job scheduling policy using workload consolidation to achieve power-aware resource allocation in a virtualized datacenter. The similar work includes [6].…”

Section: Related Workmentioning

confidence: 99%

A Novel Resource Allocation Heuristic for a Power Constrained Data Center

Zhang

Wang

Zhao

et al. 2013

2013 16th International Conference on Network-Based Information Systems

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Nowadays Internet-scale data centers are facing a severe issue, huge energy consumption, which not only increases operational cost, but also causes environment problem. For data center providers, putting power constraint on a data center may be a feasible way to keep energy consumption within an acceptable range. Hence it is commonly believed that, for a given power budget, maximizing the performance becomes an important goal for a data center, which can be achieved with well-designed resource allocation algorithm. In this paper, we discuss the resource allocation problem in a power-constrained data center, where the power consumption of whole cluster should not exceed a threshold that is set by data center provider. Then, we propose a novel resource allocation heuristic based on preference and fair allocation policy to this problem, and present further discussion and conclusion at the end.

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“…Em particular, na área de sistemas distribuídos, diversos trabalhos que propõem estratégias de escalonamento cientes do consumo de energia foram publicados nos últimos anos (Huang et al, 2006;Kim et al, 2007;Li & Li, 2010;Rodriguez et al, 2010;Ma et al, 2012;Rodriguez et al, 2012b). Essas estratégias visam minimizar o consumo de energia sem que o desempenho das aplicações seja comprometido.…”

Section: Trabalhos Relacionadosunclassified

“…Nos experimentos executados, observou-se que os algoritmos propostos proporcionaram uma redução no consumo de energia às custas de uma degradação na taxa de aceitação das aplicações. Ma et al (2012) propuseram o algoritmo EES (Energy Efficient Scheduling) para o escalon-amento de tarefas independentes em sistemas distribuídos heterogêneos de alto desempenho. O algoritmo foi projetado a partir de uma solução heurística para o problema de escalonamento ciente de consumo de energia com restrições de deadline, que foi formulado como um modelo de programação linear inteira.…”

Section: Trabalhos Relacionadosunclassified

“…Uma estratégia semelhante também é empregada em Li & Li (2010). Deve-se ressaltar, no entanto, que estratégias orientadas ao mercado são baseadas na lei da oferta e procura, sendo normalmente um processo iterativo e lento (Ma et al, 2012), que pode ser inviável em alguns cenários de grade móvel. Rodriguez et al (2010) desenvolveram o SEAS (Simple Energy-Aware Scheduler), um escalonador para grades móveis com ênfase para tarefas que exigem uso intensivo do processador.…”

Energy-efficient deadline scheduling for heterogeneous systems

Cited by 45 publications

References 48 publications

Energy-Aware Workflow Scheduling in Grid Under QoS Constraints

Energy-Aware Workflow Scheduling in Grid Under QoS Constraints

A Novel Resource Allocation Heuristic for a Power Constrained Data Center

Escalonamento em grades móveis: uma abordagem ciente do consumo de energia

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