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Exploring the Volatility of Large-Scale Shared Distributed Computing Resources

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Proceedings of International Conference on Smart Computing and Cyber Security (SMARTCYBER 2020)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 149))

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Abstract

Scientific applications often require colossal amount of computing resources for running user’s tasks. Grid computing has been proved to be powerful research testbed for accessing massive amount of computing resources at almost zero cost across various autonomous administrative institutes. It can seamlessly integrate hundreds of thousands of geographically distributed heterogeneous computing resources from multiple domains organized into virtual organization (VO). Unfortunately, existing Grid Information Service (GIS) suffers from providing exact dynamic resource information due to its scale and autonomous resource management policies. In this paper, we present a comprehensive volatility study of shared computing resources by VO in terms of characterizing resource performance related features of each computing element (CE) in computational Grids such as number of available CPU cores, average response time. We also performed experiments based on a large number of micro-benchmark tasks on real Grid environment to analyze implication of resources fluctuation. Evaluation results reveal that resource volatility studies tremendously help to decrease user response time and job completion rate.

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References

  1. C. Catlett, The philosophy of teragrid: building an open, extensible, distributed terascale facility, in 2nd IEEE/ACM International Symposium on Cluster Computing and the Grid, 2002 (IEEE, 2002), p. 8

    Google Scholar 

  2. I. Foster, C. Kesselman, S. Tuecke, The anatomy of the grid. Berman et al. [2] pp. 171–197 (2003)

    Google Scholar 

  3. M.A. Hossain, C.N. Nguyen, J.S. Kim, S. Hwang, Exploiting resource profiling mechanism for large-scale scientific computing on grids. Cluster Comput. 19(3), 1527–1539 (2016)

    Article  Google Scholar 

  4. M.A. Hossain, H.T. Vu, J.S. Kim, M. Lee, S. Hwang, Scout: a monitor and profiler of grid resources for large-scale scientific computing, in 2015 International Conference on Cloud and Autonomic Computing (ICCAC) (IEEE, 2015), pp. 260–267

    Google Scholar 

  5. B. Javadi, K. Matawie, D.P. Anderson, Modeling and analysis of resources availability in volunteer computing systems, in 2013 IEEE 32nd International Performance Computing and Communications Conference (IPCCC) (IEEE, 2013), pp. 1–9

    Google Scholar 

  6. E. Laure, B. Jones, Enabling grids for e-science: the egee project. Grid Comput. Infrastruct. Serv. Appl., 55 (2009)

    Google Scholar 

  7. R. Pordes, D. Petravick, B. Kramer, D. Olson, M. Livny, A. Roy, P. Avery, K. Blackburn, T. Wenaus, F. Wurthwein, et al., The open science grid. J. Phys. Conf. Ser. 78, 012057 (2007)

    Google Scholar 

  8. I. Raicu, I. Foster, M. Wilde, Z. Zhang, K. Iskra, P. Beckman, Y. Zhao, A. Szalay, A. Choudhary, P. Little et al., Middleware support for many-task computing. Cluster Comput. 13(3), 291–314 (2010)

    Article  Google Scholar 

  9. I. Raicu, I. Foster, Y. Zhao, Many-task computing for grids and supercomputers, in Proceedings of the Workshop on Many-Task Computing on Grids and Supercomputers (MTAGS’08) (Nov 2008)

    Google Scholar 

  10. I. Rodero, D. Villegas, N. Bobro, Y. Liu, L. Fong, S.M. Sadjadi, Enabling interoperability among grid meta-schedulers. J. Grid Comput. 11(2), 311–336 (2013)

    Article  Google Scholar 

  11. H. Sanjay, S. Vadhiyar, Performance modeling of parallel applications for grid scheduling. J. Parallel Distrib. Comput. 68(8), 1135–1145 (2008)

    Article  Google Scholar 

  12. The biomed Virtual Organization: Available at https://lsgc.org/en/Biomed:home

  13. Y. Wu, K. Hwang, Y. Yuan, W. Zheng, Adaptive workload prediction of grid performance in condence windows. IEEE Trans. Parallel Distrib. Syst. 21(7), 925–938 (2010)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Computer Engineering, Kyungdong University, Global Campus (Goseong), Goseong, Gangwon-do, Republic of Korea

    Md Azam Hossain & Baseem Al-athwari

  2. Department of Computer Engineering, Myongji University, Yongin, Republic of Korea

    Jik-soo Kim

  3. Korea Institute of Science and Technology Information (KISTI), Daejeon, Republic of Korea

    Soonwook Hwang

Authors
  1. Md Azam Hossain
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  2. Baseem Al-athwari
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  3. Jik-soo Kim
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  4. Soonwook Hwang
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Corresponding author

Correspondence to Md Azam Hossain .

Editor information

Editors and Affiliations

  1. School of Computer Engineering, Kalinga Institute of Industrial Technology, KIIT Deemed to be University, Bhubaneswar, India

    Prasant Kumar Pattnaik

  2. Division of Information and Communication Engineering, Dongseo University, Busan, Korea (Republic of)

    Mangal Sain

  3. Department of Smart Computing, Kyungdong University Global Campus, Gangwondo, Korea (Republic of)

    Ahmed A. Al-Absi

  4. Department of Computer Science, Swansea University, Bay Campus, Swansea, UK

    Pardeep Kumar

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© 2021 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Hossain, M.A., Al-athwari, B., Kim, Js., Hwang, S. (2021). Exploring the Volatility of Large-Scale Shared Distributed Computing Resources. In: Pattnaik, P.K., Sain, M., Al-Absi, A.A., Kumar, P. (eds) Proceedings of International Conference on Smart Computing and Cyber Security. SMARTCYBER 2020. Lecture Notes in Networks and Systems, vol 149. Springer, Singapore. https://doi.org/10.1007/978-981-15-7990-5_26

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