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Reseach Article

Performance Analysis of Adaptive Resource Clustering in Grid

by Ashish Chandak, Bibhudatta Sahoo, Ashok Kumar Turuk
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 29 - Number 9
Year of Publication: 2011
Authors: Ashish Chandak, Bibhudatta Sahoo, Ashok Kumar Turuk
10.5120/3588-4973

Ashish Chandak, Bibhudatta Sahoo, Ashok Kumar Turuk . Performance Analysis of Adaptive Resource Clustering in Grid. International Journal of Computer Applications. 29, 9 ( September 2011), 41-47. DOI=10.5120/3588-4973

@article{ 10.5120/3588-4973,
author = { Ashish Chandak, Bibhudatta Sahoo, Ashok Kumar Turuk },
title = { Performance Analysis of Adaptive Resource Clustering in Grid },
journal = { International Journal of Computer Applications },
issue_date = { September 2011 },
volume = { 29 },
number = { 9 },
month = { September },
year = { 2011 },
issn = { 0975-8887 },
pages = { 41-47 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume29/number9/3588-4973/ },
doi = { 10.5120/3588-4973 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:15:23.830868+05:30
%A Ashish Chandak
%A Bibhudatta Sahoo
%A Ashok Kumar Turuk
%T Performance Analysis of Adaptive Resource Clustering in Grid
%J International Journal of Computer Applications
%@ 0975-8887
%V 29
%N 9
%P 41-47
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

A grid provides abundant resources to the grid users. Task scheduling is a fundamental issue in grid computing. The objective of task scheduling is to allocate required resources to user request. Grid application that requires fast task execution does not perform well since tasks are assigned according to node availability not according to node computing capability. In this paper, we discussed adaptive resource clustering architecture that virtually grouping same computing capability nodes based on the number and resource requirement of tasks so that task execution becomes faster. In this paper, we evaluate the performance of adaptive clustering with static and without clustering of resources and task are schedule by Max-Min, Min-Min, FCFS heuristics and simulation results shows that our architecture outperforms in makespan and success execution rate of tasks.

References
  1. Ian Foster, Carl Kesselman, and Steven Tuecke, The anatomy of the grid: Enabling scalable virtual organizations, International Journal High Performane Computing Application 15, 200-222, 2001.
  2. Carl Kesselman Ian Foster. The Grid 2: Blueprint for a New Computing Infrastructure. ELSEVIER, Second edition.
  3. S D Sharma. Operation Research. Kedar Nath Ram Nath and Co, Fourteenth edition, 2001.
  4. Tracy D. Braun, Howard Jay Siegel, and Noah Beck, A Comparison of Eleven Static Heuristics for Mapping a Class of Independent Tasks onto Heterogeneous Distributed Computing Systems, Journal of Parallel and Distributed Computing, 810-837, 2001.
  5. L. Ramakrishnan, L. Grit, A. Iamnitchi, D. Irwin, A. Yumerefendi, J. Chase. Toward a Doctrine of Containment: Grid Hosting with Adaptive Resource Control. IEEE/ACM SuperComputing.
  6. K. Appleby, S. Fakhouri, L. Fong, G. Goldszmidt, M. Kalantar, S. Krishnakumar, D. Pazel, J. Pershing, and B. Rochwerger, Oceano - SLA Based Management of a Computing Utility, In 7th IFIP/IEEE International Symposium on Integrated Network Management.
  7. Y. He, W.J. Hsu, C.E. Leiserson, Provably efficient online nonclairvoyant adaptive scheduling, IEEE Trans. Parallel Distrib. Syst. 19, 1263-1279, 2008.
  8. F. Xhafa, L. Barolli, A. Durresi, Immediate mode scheduling of independent jobs in computational grids, in: Proceedings of the 21st International Conference on Advanced Networking and Applications (AINA '07), IEEE, 970-977, 2007.
  9. F. Xhafa, L. Barolli, A. Durresi, Batch mode scheduling in grid systems, Int. J. Web Grid Serv. 3 19-37, 2007.
  10. Kobra Etminani, M. Naghibzadeh, A Min-Min Max-Min Selective Algorihtm for Grid Task Scheduling., ICI 2007. 3rd IEEE/IFIP International Conference in Central Asia, 2007.
  11. Hesam Izakian and Ajith Abraham and Behrouz Tork Ladani, An Auction Method for Resource Allocation in Computational Grids, Future Generation Computer Systems, 26, 228 - 235, 2010.
  12. J. Bresnahan, I. Foster. An Architecture for Dynamic Allocation of Compute Cluster Bandwidth, MS Thesis, Department of Computer Science, University of Chicago, December 2006.
  13. H.D. Karatza, A simulation model of task cluster scheduling in distributed systems, in: Proceedings of the 7th IEEE Workshop on Future Trends of Distributed Computing Systems (FTDCS’99), December 20–22, 1999, Cape Town, IEEE Computer Society Press, 163–168, 1999.
  14. Kyriaki Gkoutioudi, Helen D. Karatza, Task cluster scheduling in a grid system, Simulation Modelling Practice and Theory, 18, 1242–1252, 2010.
  15. A. Gerasoulis, T. Yang, On the granularity and clustering of directed acyclic task graphs, IEEE Transactions on Parallel and Distributed Systems 4 (6), 686–701, 1993.
  16. S.P. Dandamudi, Performance implications of task routing and task scheduling strategies for multiprocessor systems, in: Proceedings of the IEEE Euromicro Conference on Massively Parallel Computing Systems, Ischia, Italy, 348–353, 1994.
  17. H.D. Karatza, A Comparative analysis of scheduling policies in a distributed system using simulation, International Journal of Simulation Systems, Science and Technology 1, 12–20, 2000.
  18. L.W. Dowdy, E. Rosti, G. Serazzi, E. Smirni, Scheduling Issues in high-performance computing, Performance Evaluation Review 26, 60–69, 1999.
Index Terms

Computer Science
Information Sciences

Keywords

Task Scheduling Adaptive Resource Clustering Task Clustering Success Execution Rate