The energy efficient approach to assigning tasks in a server cluster
Keywords:
energy efficiency, performance, server cluster, task distribution, data processing
Abstract
The approach to increasing energy efficiency of the data center computing by using energy efficient tasks scheduling within the server cluster as an integral part of the data center infrastructure has been described in the paper. The proposed approach is characterized by taking into account both energy efficiency and performance parameters. The approach is implemented in the task scheduling algorithm. The main idea of the algorithm is to carry out the preliminary attestation of each cluster nodes individually. The efficiency of the proposed approach has been tested by the simulation process and proved experimentally. The approach has shown a gain of up to 49,09% by the performance criteria and up to 9,04% by the energy efficiency criteria for big heterogeneous clusters.Downloads
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References
Koomey J. G., Worldwide electricity used in data centers / J. Koomey // Environmental Research Letters, vol. 3, no. 3, p., 2008.
Beloglazov A. Energy-Efficient Management of Virtual Machines in Data Centers for Cloud Computing / Beloglazov Anton – Melbourne, 2013.
Hosseinimotlagh S. A Cooperative Two-Tier Energy-Aware Scheduling for Real-Time Tasks in Computing Clouds / S. Hosseinimotlagh, F. Khunjush, S. Hosseinimotlagh. // Euromicro International Conference on Parallel, Distributed, and Network-Based Processing. – 2014. – №22. – С. 178–182.
An Energy and Deadline Aware Resource Provisioning, Scheduling and Optimization Framework for Cloud Systems / Y.Gao, Y. Wang, S. K. Gupta, M. Pedram. // IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis. – 2013. – №9. – С. 31:1–31:10
Min_ с: стратегия неоднородной концентрации задач для энергосберегающих компьютерных расписаний / [Ф. Армента-Кано, А. Черных, Х. М. Кортес-Мендоза та ін.]. // Труды ИСП РАН. – 2015. – №6. – С. 355.
Liu N. Task Scheduling and Server Provisioning for Energy-Efficient Cloud-Computing Data Centers / N. Liu, Z. Dong, R. Rojas-Cessa. // IEEE 33rd International Conference on Distributed Computing Systems Workshops. – 2013. – №33. – С. 226–231.
Грушин Д. А. Энергоэффективные вычисления для группы кластеров / Д. А. Грушин, Н. Н. Кузюрин. – Москва, 2013. – 433 с.
Stress-test, POSIX [Електронний ресурс] – Режим доступу до ресурсу: https://people.seas.harvard.edu/~apw/stress/.
Jyoti V. Comparative Study of Load Balancing Algorithms / V. Jyoti, K. J. Anant. // IOSR Journal of Engineering (IOSRJEN). – 2013. – С. 45–50.
Проектирование ЦОД и строительство дата-центра [Електронний ресурс] – Режим доступу до ресурсу: http://www.datacenter-ts.ru/.
Beloglazov A. Energy-Efficient Management of Virtual Machines in Data Centers for Cloud Computing / Beloglazov Anton – Melbourne, 2013.
Hosseinimotlagh S. A Cooperative Two-Tier Energy-Aware Scheduling for Real-Time Tasks in Computing Clouds / S. Hosseinimotlagh, F. Khunjush, S. Hosseinimotlagh. // Euromicro International Conference on Parallel, Distributed, and Network-Based Processing. – 2014. – №22. – С. 178–182.
An Energy and Deadline Aware Resource Provisioning, Scheduling and Optimization Framework for Cloud Systems / Y.Gao, Y. Wang, S. K. Gupta, M. Pedram. // IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis. – 2013. – №9. – С. 31:1–31:10
Min_ с: стратегия неоднородной концентрации задач для энергосберегающих компьютерных расписаний / [Ф. Армента-Кано, А. Черных, Х. М. Кортес-Мендоза та ін.]. // Труды ИСП РАН. – 2015. – №6. – С. 355.
Liu N. Task Scheduling and Server Provisioning for Energy-Efficient Cloud-Computing Data Centers / N. Liu, Z. Dong, R. Rojas-Cessa. // IEEE 33rd International Conference on Distributed Computing Systems Workshops. – 2013. – №33. – С. 226–231.
Грушин Д. А. Энергоэффективные вычисления для группы кластеров / Д. А. Грушин, Н. Н. Кузюрин. – Москва, 2013. – 433 с.
Stress-test, POSIX [Електронний ресурс] – Режим доступу до ресурсу: https://people.seas.harvard.edu/~apw/stress/.
Jyoti V. Comparative Study of Load Balancing Algorithms / V. Jyoti, K. J. Anant. // IOSR Journal of Engineering (IOSRJEN). – 2013. – С. 45–50.
Проектирование ЦОД и строительство дата-центра [Електронний ресурс] – Режим доступу до ресурсу: http://www.datacenter-ts.ru/.
Published
2017-10-27
How to Cite
Глоба, Л. С., Гвоздецька, Н. А., Прокопець, В. А., & Степурін, О. В. (2017). The energy efficient approach to assigning tasks in a server cluster. Bulletin of V.N. Karazin Kharkiv National University, Series «Mathematical Modeling. Information Technology. Automated Control Systems», 34, 18-28. Retrieved from https://periodicals.karazin.ua/mia/article/view/9836
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