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Power efficient scheduling heuristics for energy conservation in computational grids

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Abstract

Computation grids and computational clouds are becoming increasingly popular in the organizations which require massive computational capabilities. Building such infrastructures makes a lucrative business case, thanks to availability of cheap hardware components and affordable software. Maintaining computational grids or cloud, however, require careful planning as in such dedicated environments, round-the-clock availability of workstations is very crucial. Ensuring uninterrupted availability, not only demands mechanism for failover redundancy but also results in constant power drainage. The tradeoff between the cost and the performance is the constant dilemma that the operations of the data centers face today. In this paper, we propose various heuristics for power-aware scheduling algorithms for scheduling jobs with dependent tasks onto the computational grid. We formulate the problem as a multi-objective function which results in various cost-performance tradeoffs each lying within the solution boundary.

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References

  1. Karabuto A (2007) HDD diet: power consumption and heat dissipation, September 2007. http://www.digit-life.com/articles2/storage/hddpower.html

  2. Rajamani K, Lefurgy C (2003) On evaluating request-distribution schemes for saving energy in server clusters. In: IEEE international symposium on performance analysis of systems and software (ISPASS’03), March 2003

  3. Burke J (2007) New data center metrics that matter: New measures of efficiency in data centers, September 2007. http://www.networkworld.com/newsletters/datacenter/2007/0625datacenter1.html

  4. The Green Grid (2007) The green grid metrics: describing data center power efficiency. September 2007. http://www.thegreengrid.org/gg_content/

  5. AMD White Paper (2007) Power and cooling in data centers, September 2007. http://enterprise.amd.com/Downloads/34146A_PC_WP_en.pdf

  6. Dhodapkar A, Smith JE (2002) Managing multi-configuration hardware via dynamic working set analysis. In: Proceedings of the 29th international symposium on computer architecture, May 2002

    Google Scholar 

  7. Lebeck AR, Fan X, Zeng H, Ellis CS (2000) Power aware page allocation. In: Architectural support for programming languages and operating systems

    Google Scholar 

  8. Aziz A, El-Rewini H Grid resource allocation and task scheduling for resource intensive application. Workshop on parallel and distributed multimedia (PDM). In: conjunction with International Conference on Parallel Processing (ICPP) ’06

  9. Aziz A, El-Rewini H Workflow scheduling in computational grids: opportunistic vs. planned. In: The sixth ACS/IEEE international conference on computer systems and applications (AICCSA-08)

  10. Aziz A, El-Rewini H (2008) On the use of meta-heuristics to increase the efficiency of online grid workflow scheduling algorithms. Clust Comput J 11(4)

  11. Deb K (2001) Multi-objective optimization using evolutionary algorithms. Wiley, New York

    MATH  Google Scholar 

  12. Aziz A, El-Rewini H (2009) Power aware scheduling in computational grids. In: The 2009 international conference on parallel and distributed processing and techniques and applications (PDPTA’09)

    Google Scholar 

  13. Khan SU, Ahmad I (2009) A pure Nash equilibrium-based game theoretical method for data replication across multiple servers. IEEE Transactions on Knowledge and Data Engineering, 21(4):537–553

    Article  MathSciNet  Google Scholar 

  14. Ghasemi A, Faez K (2008) A Nash power-aware MAC game for ad-hoc wireless networks. In: IEEE 19th international symposium on personal, indoor and mobile radio communications

    Google Scholar 

  15. Ahmad I, Ranka S, Khan S (2008) Using game theory for scheduling tasks on a multi-core processors for simultaneous optimization of performance and energy. In: IEEE international symposium on parallel and distributed processing

    Google Scholar 

  16. Khargharia B, Hariri S, Szidarovszky F, Houri M, El-Rewini H, Khan SU, Ahmad I, Yousif MS (2007) Autonomic power and performance management for large-scale data centers. In: IEEE international symposium on parallel and distributed processing

    Google Scholar 

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Authors and Affiliations

  1. Department of Computer Science, National University of Computer and Emerging Sciences (FAST-NU), Lahore, Pakistan

    Abdul Aziz

  2. School of Engineering and Mines, University of North Dakota, Grand Forks, ND, USA

    Hesham El-Rewini

Authors
  1. Abdul Aziz
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  2. Hesham El-Rewini
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Correspondence to Abdul Aziz.

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Aziz, A., El-Rewini, H. Power efficient scheduling heuristics for energy conservation in computational grids. J Supercomput 57, 65–80 (2011). https://doi.org/10.1007/s11227-011-0559-7

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  • DOI: https://doi.org/10.1007/s11227-011-0559-7

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