• Previous Article
    Analysis and optimization of a gated polling based spectrum allocation mechanism in cognitive radio networks
  • JIMO Home
  • This Issue
  • Next Article
    Analysis of an M/M/1 queue with vacations and impatience timers which depend on the server's states
April  2016, 12(2): 667-685. doi: 10.3934/jimo.2016.12.667

Effect of energy-saving server scheduling on power consumption for large-scale data centers

1. 

Graduate School of Informatics, Kyoto University, Yoshida-Honmachi, Sakyo-ku, Kyoto 606-8501, Japan

2. 

Graduate School of Information Science, Nara Institute of Science and Technology, 8916-5 Takayama, Ikoma, Nara 630-0192

Received  October 2014 Revised  March 2015 Published  June 2015

Large-scale data centers for cloud computing services consist of a number of commodity servers, resulting in a huge amount of power consumption. In order to save power consumption, BEEMR (Berkeley Energy Efficient MapReduce), a MapReduce workload manager, is proposed. In a BEEMR-based data center, servers are allocated to either of the interactive and batch zones. Arriving jobs of a small size begin to be processed immediately in the interactive zone, while large-sized jobs are queued and served simultaneously at every fixed service period in the batch zone. In this paper, we analyze the performance of BEEMR-type job scheduling. We consider two queueing models for the interactive and batch zones. The interactive zone is modeled as a single-server queueing system with processor-sharing (PS) service. In terms of the batch zone, we consider a queueing system with gated service in which arriving jobs are queued and begin to be served when a fixed service period starts. For these models, the time-average power consumption and the mean response time are derived. Numerical examples show that the power consumption is significantly affected by the allocation of servers to both zones, while the power consumption is insensitive to the length of the batch-service period.
Citation: Masataka Kato, Hiroyuki Masuyama, Shoji Kasahara, Yutaka Takahashi. Effect of energy-saving server scheduling on power consumption for large-scale data centers. Journal of Industrial & Management Optimization, 2016, 12 (2) : 667-685. doi: 10.3934/jimo.2016.12.667
References:
[1]

S. Asmussen, Applied Probability and Queues,, $2^{nd}$ edition, (2003). Google Scholar

[2]

K. E. Avrachenkov, U. Ayesta, P. Brown and R. Núñez-Queija, Discriminatory processor sharing revisited,, in Proc. IEEE INFOCOM'05, (2005), 784. doi: 10.1109/INFCOM.2005.1498310. Google Scholar

[3]

L. A. Barroso and U. Hölzle, The Datacenter as a Computer: An Introduction to the Design of Warehouse-Scale Machines,, Morgan & Claypool, (2009). doi: 10.2200/S00193ED1V01Y200905CAC006. Google Scholar

[4]

P. Bremaud, Markov Chains, Gibbs Fields, Monte Carlo Simulation, and Queues,, Springer, (1999). doi: 10.1007/978-1-4757-3124-8. Google Scholar

[5]

L. Breuer and D. Baum, An Introduction to Queueing Theory and Matrix-Analytic Methods,, Springer, (2005). Google Scholar

[6]

R. Brown, E. Masanet, B. Nordman, W. Tschudi, A. Shehabi, J. Stanley, J. Koomey, D. Sartor, P. Chan, J. Loper, S. Capana, B. Hedman, R. Duff, E. Haines, D. Sass and A. Fanara, Report to congress on server and data center energy efficiency: Public law 109-431,, Lawrence Berkeley National Laboratory, (2007). Google Scholar

[7]

Y. Chen, S. Alspaugh, D. Borthakur and R. Katz, Energy efficiency for large-scale MapReduce workloads with significant interactive analysis,, in Proc. The European Professional Society on Computer Systems 2012, (2012), 43. doi: 10.1145/2168836.2168842. Google Scholar

[8]

D. Gibson and E. Seneta, Monotone infinite stochastic matrices and their augmented truncations,, Stochastic Processes and their Applications, 24 (1987), 287. doi: 10.1016/0304-4149(87)90019-6. Google Scholar

[9]

H. Masuyama, Error bounds for augmented truncations of discrete-time block-monotone Markov chains under geometric drift conditions,, Accepted for publication in Advances in Applied Probability, (). doi: 10.1239/aap/1427814582. Google Scholar

[10]

S. Pelley, D. Meisner, T. F. Wenisch and J. W. VanGilder, Understanding and abstracting total data center power,, in Proc. Workshop on Energy-Efficient Design 2009, (2009). Google Scholar

[11]

M. Sakata, S. Noguchi and J. Oizumi, An analysis of the M/G/1 queue under round-robin scheduling,, Operations Research, 19 (1971), 371. Google Scholar

[12]

C. Schwarts, R. Pries and P. Tran-Gia, A queuing analysis of an energy-saving mechanism in data centers,, in Proc. International Conference on Information Networking 2012, (2012), 70. doi: 10.1109/ICOIN.2012.6164352. Google Scholar

[13]

R. L. Tweedie, Truncation approximations of invariant measures for Markov chains,, Journal of Applied Probability, 35 (1998), 517. doi: 10.1239/jap/1032265201. Google Scholar

[14]

R. W. Wolff, Stochastic Modeling and the Theory of Queues,, Prentice-hall, (1989). Google Scholar

show all references

References:
[1]

S. Asmussen, Applied Probability and Queues,, $2^{nd}$ edition, (2003). Google Scholar

[2]

K. E. Avrachenkov, U. Ayesta, P. Brown and R. Núñez-Queija, Discriminatory processor sharing revisited,, in Proc. IEEE INFOCOM'05, (2005), 784. doi: 10.1109/INFCOM.2005.1498310. Google Scholar

[3]

L. A. Barroso and U. Hölzle, The Datacenter as a Computer: An Introduction to the Design of Warehouse-Scale Machines,, Morgan & Claypool, (2009). doi: 10.2200/S00193ED1V01Y200905CAC006. Google Scholar

[4]

P. Bremaud, Markov Chains, Gibbs Fields, Monte Carlo Simulation, and Queues,, Springer, (1999). doi: 10.1007/978-1-4757-3124-8. Google Scholar

[5]

L. Breuer and D. Baum, An Introduction to Queueing Theory and Matrix-Analytic Methods,, Springer, (2005). Google Scholar

[6]

R. Brown, E. Masanet, B. Nordman, W. Tschudi, A. Shehabi, J. Stanley, J. Koomey, D. Sartor, P. Chan, J. Loper, S. Capana, B. Hedman, R. Duff, E. Haines, D. Sass and A. Fanara, Report to congress on server and data center energy efficiency: Public law 109-431,, Lawrence Berkeley National Laboratory, (2007). Google Scholar

[7]

Y. Chen, S. Alspaugh, D. Borthakur and R. Katz, Energy efficiency for large-scale MapReduce workloads with significant interactive analysis,, in Proc. The European Professional Society on Computer Systems 2012, (2012), 43. doi: 10.1145/2168836.2168842. Google Scholar

[8]

D. Gibson and E. Seneta, Monotone infinite stochastic matrices and their augmented truncations,, Stochastic Processes and their Applications, 24 (1987), 287. doi: 10.1016/0304-4149(87)90019-6. Google Scholar

[9]

H. Masuyama, Error bounds for augmented truncations of discrete-time block-monotone Markov chains under geometric drift conditions,, Accepted for publication in Advances in Applied Probability, (). doi: 10.1239/aap/1427814582. Google Scholar

[10]

S. Pelley, D. Meisner, T. F. Wenisch and J. W. VanGilder, Understanding and abstracting total data center power,, in Proc. Workshop on Energy-Efficient Design 2009, (2009). Google Scholar

[11]

M. Sakata, S. Noguchi and J. Oizumi, An analysis of the M/G/1 queue under round-robin scheduling,, Operations Research, 19 (1971), 371. Google Scholar

[12]

C. Schwarts, R. Pries and P. Tran-Gia, A queuing analysis of an energy-saving mechanism in data centers,, in Proc. International Conference on Information Networking 2012, (2012), 70. doi: 10.1109/ICOIN.2012.6164352. Google Scholar

[13]

R. L. Tweedie, Truncation approximations of invariant measures for Markov chains,, Journal of Applied Probability, 35 (1998), 517. doi: 10.1239/jap/1032265201. Google Scholar

[14]

R. W. Wolff, Stochastic Modeling and the Theory of Queues,, Prentice-hall, (1989). Google Scholar

[1]

Kyosuke Hashimoto, Hiroyuki Masuyama, Shoji Kasahara, Yutaka Takahashi. Performance analysis of backup-task scheduling with deadline time in cloud computing. Journal of Industrial & Management Optimization, 2015, 11 (3) : 867-886. doi: 10.3934/jimo.2015.11.867

[2]

Tuan Phung-Duc, Wouter Rogiest, Sabine Wittevrongel. Single server retrial queues with speed scaling: Analysis and performance evaluation. Journal of Industrial & Management Optimization, 2017, 13 (4) : 1927-1943. doi: 10.3934/jimo.2017025

[3]

Shunfu Jin, Wuyi Yue. Performance analysis and evaluation for power saving class type III in IEEE 802.16e network. Journal of Industrial & Management Optimization, 2010, 6 (3) : 691-708. doi: 10.3934/jimo.2010.6.691

[4]

Tsuguhito Hirai, Hiroyuki Masuyama, Shoji Kasahara, Yutaka Takahashi. Performance analysis of large-scale parallel-distributed processing with backup tasks for cloud computing. Journal of Industrial & Management Optimization, 2014, 10 (1) : 113-129. doi: 10.3934/jimo.2014.10.113

[5]

Shunfu Jin, Haixing Wu, Wuyi Yue, Yutaka Takahashi. Performance evaluation and Nash equilibrium of a cloud architecture with a sleeping mechanism and an enrollment service. Journal of Industrial & Management Optimization, 2017, 13 (5) : 1-18. doi: 10.3934/jimo.2019060

[6]

Shunfu Jin, Wuyi Yue, Xuena Yan. Performance evaluation of a power saving mechanism in IEEE 802.16 wireless MANs with bi-directional traffic. Journal of Industrial & Management Optimization, 2011, 7 (3) : 717-733. doi: 10.3934/jimo.2011.7.717

[7]

Jinsong Xu. Reversible hidden data access algorithm in cloud computing environment. Discrete & Continuous Dynamical Systems - S, 2019, 12 (4&5) : 1219-1232. doi: 10.3934/dcdss.2019084

[8]

Zhanyou Ma, Wuyi Yue, Xiaoli Su. Performance analysis of a Geom/Geom/1 queueing system with variable input probability. Journal of Industrial & Management Optimization, 2011, 7 (3) : 641-653. doi: 10.3934/jimo.2011.7.641

[9]

Sin-Man Choi, Ximin Huang, Wai-Ki Ching. Minimizing equilibrium expected sojourn time via performance-based mixed threshold demand allocation in a multiple-server queueing environment. Journal of Industrial & Management Optimization, 2012, 8 (2) : 299-323. doi: 10.3934/jimo.2012.8.299

[10]

Omer Faruk Yilmaz, Mehmet Bulent Durmusoglu. A performance comparison and evaluation of metaheuristics for a batch scheduling problem in a multi-hybrid cell manufacturing system with skilled workforce assignment. Journal of Industrial & Management Optimization, 2018, 14 (3) : 1219-1249. doi: 10.3934/jimo.2018007

[11]

Zhanqiang Huo, Wuyi Yue, Naishuo Tian, Shunfu Jin. Performance evaluation for the sleep mode in the IEEE 802.16e based on a queueing model with close-down time and multiple vacations. Journal of Industrial & Management Optimization, 2009, 5 (3) : 511-524. doi: 10.3934/jimo.2009.5.511

[12]

Zhanyou Ma, Wenbo Wang, Linmin Hu. Performance evaluation and analysis of a discrete queue system with multiple working vacations and non-preemptive priority. Journal of Industrial & Management Optimization, 2017, 13 (5) : 1-14. doi: 10.3934/jimo.2018196

[13]

Zhanyou Ma, Pengcheng Wang, Wuyi Yue. Performance analysis and optimization of a pseudo-fault Geo/Geo/1 repairable queueing system with N-policy, setup time and multiple working vacations. Journal of Industrial & Management Optimization, 2017, 13 (3) : 1467-1481. doi: 10.3934/jimo.2017002

[14]

Sho Nanao, Hiroyuki Masuyama, Shoji Kasahara, Yutaka Takahashi. Queueing analysis of data block synchronization mechanism in peer-to-peer based video streaming system. Journal of Industrial & Management Optimization, 2011, 7 (3) : 699-716. doi: 10.3934/jimo.2011.7.699

[15]

Weidong Bao, Haoran Ji, Xiaomin Zhu, Ji Wang, Wenhua Xiao, Jianhong Wu. ACO-based solution for computation offloading in mobile cloud computing. Big Data & Information Analytics, 2016, 1 (1) : 1-13. doi: 10.3934/bdia.2016.1.1

[16]

Serap Ergün, Bariş Bülent Kırlar, Sırma Zeynep Alparslan Gök, Gerhard-Wilhelm Weber. An application of crypto cloud computing in social networks by cooperative game theory. Journal of Industrial & Management Optimization, 2017, 13 (5) : 1-15. doi: 10.3934/jimo.2019036

[17]

Tsuguhito Hirai, Hiroyuki Masuyama, Shoji Kasahara, Yutaka Takahashi. Performance optimization of parallel-distributed processing with checkpointing for cloud environment. Journal of Industrial & Management Optimization, 2018, 14 (4) : 1423-1442. doi: 10.3934/jimo.2018014

[18]

Shunfu Jin, Wuyi Yue, Zhanqiang Huo. Performance evaluation for connection oriented service in the next generation Internet. Numerical Algebra, Control & Optimization, 2011, 1 (4) : 749-761. doi: 10.3934/naco.2011.1.749

[19]

Shunfu Jin, Wuyi Yue, Chao Meng, Zsolt Saffer. A novel active DRX mechanism in LTE technology and its performance evaluation. Journal of Industrial & Management Optimization, 2015, 11 (3) : 849-866. doi: 10.3934/jimo.2015.11.849

[20]

Keiji Tatsumi, Masashi Akao, Ryo Kawachi, Tetsuzo Tanino. Performance evaluation of multiobjective multiclass support vector machines maximizing geometric margins. Numerical Algebra, Control & Optimization, 2011, 1 (1) : 151-169. doi: 10.3934/naco.2011.1.151

2018 Impact Factor: 1.025

Metrics

  • PDF downloads (11)
  • HTML views (0)
  • Cited by (0)

[Back to Top]