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Reseach Article

Load Balancing Approaches in Grid Computing Environment

by Neeraj Pandey, Shashi Kant Verma, Vivek Kumar Tamta
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 72 - Number 12
Year of Publication: 2013
Authors: Neeraj Pandey, Shashi Kant Verma, Vivek Kumar Tamta
10.5120/12549-9185

Neeraj Pandey, Shashi Kant Verma, Vivek Kumar Tamta . Load Balancing Approaches in Grid Computing Environment. International Journal of Computer Applications. 72, 12 ( June 2013), 42-49. DOI=10.5120/12549-9185

@article{ 10.5120/12549-9185,
author = { Neeraj Pandey, Shashi Kant Verma, Vivek Kumar Tamta },
title = { Load Balancing Approaches in Grid Computing Environment },
journal = { International Journal of Computer Applications },
issue_date = { June 2013 },
volume = { 72 },
number = { 12 },
month = { June },
year = { 2013 },
issn = { 0975-8887 },
pages = { 42-49 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume72/number12/12549-9185/ },
doi = { 10.5120/12549-9185 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:38:48.916692+05:30
%A Neeraj Pandey
%A Shashi Kant Verma
%A Vivek Kumar Tamta
%T Load Balancing Approaches in Grid Computing Environment
%J International Journal of Computer Applications
%@ 0975-8887
%V 72
%N 12
%P 42-49
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Grid computing is a kind of distributed computing that involve the integrated and collaborative use of distributed resources. It involves huge amounts of computational task which require reliable resource sharing across computing domains. Load balancing in grid is a technique which distributes the workloads across multiple computing nodes to get optimal resource utilization, minimum time delay, maximize throughput and avoid overload. It is a challenging problem that has been studied extensively is the past several years. This paper attempts to provide a comprehensive overview of load balancing in grid computing environment and also analyses the job distribution and system behavior. Furthermore, this survey various load balancing algorithms for the grid computing environment, identify several comparison metrics for the load balancing algorithms and carry out the comparison based on these identified metrics between them. it also reviews the latest research activities in the area of grid computing, including characteristics, capabilities, architecture, applications, design constraints, scheduling and load balancing and presents a set of challenges and problems.

References
  1. I. Foster, C. Kesselman, and S. Tuecke, The anatomy of the grid: Enabling scalable virtual organizations, The International Journal of High Performance Computing Applications, 15 (3) (2001) 200-222.
  2. Rajkumar Buyya, and Srikumar Venugopal, A Gentle Introduction to Grid Computing and Technologies, Computer Socity of India, CSI Communication, July (2005).
  3. Yajun Li, Yuhang Yang, Maode Ma, and Liang Zhoy, A hybrid load balancing strategy of sequential tasks for grid computing environments, Future Generation Computer Systems, 25 (2009) 819-828
  4. Albert Y. Zomaya, Yee-Hwei Teh, Observations on Using Genetic Algorithms for Dynamic Load-Balancing, IEEE Transections on Parallel and Distributed System, Vol. 12, No. 9, Sept. (2001) 899-911.
  5. Menno Dobber, Rob van der Mei, Ger Koole, Dynamic Load Balancing and Job Replication in a Global-Scale Grid Environment: A Comparison, IEEE Transections on Parallel and Distributed System, Vol. 20, No. 2, Feb. (2009) 207-218.
  6. Yu-Kwong Kwok, Lap-Sun Cheung, A new fuzzy-decision based load balancing system for distributed object computing, Journal of Parallel and Distributed Computing, 64 (2004) 238–253
  7. Mika Rantonen, Tapio Frantti, Kauko Leiviska, Fuzzy expert system for load balancing in symmetric multiprocessor systems, Expert Systems with Applications 37 (2010) 8711–8720.
  8. R. P. Prado, S. Garcia-Galan, A. J. Yuste, and J. E. Munoz Exposito, A fuzzy rule-based meta-schedular with evolutionary learning for grid computing, Engineering Applications of Artificial Intelligence 23 (2010) 1072–1082.
  9. Tony Hey, Anne E. Trefethen, The UK e-Science Core Programme and the Grid, Future Generation Computer Systems 18 (2002) 1017–1031.
  10. Junwei Caoa, Daniel P. Spooner, Stephen A. Jarvis, Graham R. Nudd, Grid load balancing using intelligent agents, Future Generation Computer Systems 21 (2005) 135–149.
  11. K. Q. Yan, S. C. Wang, C. P. Chang, J. S. Lin, A hybrid load balancing policy underlying grid computing environment, Computer Standards & Interfaces 29 (2007) 161–173.
  12. Jun Wang, Jian-Wen Chen, Yong-Liang Wang, Di Zheng, Intelligent Load Balancing Strategies for Complex Distributed Simulation Applications, 2009 International Conference on Computational Intelligence and Security, 2009 (182-186).
  13. Kuo-Qin Yan, Shun-Sheng Wang, Shu-Ching Wang, Chiu-Ping Chang, Towards a hybrid load balancing policy in grid computing system, Expert Systems with Applications 36 (2009) 12054–12064.
  14. Sonesh Surana, Brighten Godfrey, Karthik Lakshminarayanan, Richard Karp, Ion Stoica, Load balancing in dynamic structured peer-to-peer systems, Journal of Performance Evaluation 63 (2006) 217–240.
  15. Luis Miguel Campos, Isaac D. Scherson, Rate of change load balancing in distributed and parallel systems, Parallel Computing 26 (2000) 1213-1230.
  16. Karen D. Devine, Erik G. Boman, Robert T. Heaphy, Bruce A. Hendrickson, James D. Teresco, Jamal Faik, Joseph E. Flaherty, Luis G. Gervasio, New challenges in dynamic load balancing, Applied Numerical Mathematics 52 (2005) 133–152.
  17. Arjen Schoneveld, Peter M. A. Sloot, Martin Lees, Erwan Karyadi, A framework for dynamic load balancing: A case study on explosive containment simulation, Parallel Computing 26 (2000) 737-751.
  18. Xiao Qin, Performance comparisons of load balancing algorithms for I/O-intensive workloads on clusters, Journal of Network and Computer Applications 31 (2008) 32–46.
  19. Daniel Grosu, Anthony T. Chronopoulos, Noncooperative load balancing in distributed systems, Journal of Parallel and Distributed Computing 65 (2005) 1022 – 1034.
  20. Yin-Fu Huang, Chih-Chiang Fang, Load balancing for clusters of VOD servers, Information Sciences 164 (2004) 113–138.
  21. Qingqi Long, Jie Lin, Zhixun Sun, Agent scheduling model for adaptive dynamic load balancing in agent-based distributed simulations, Simulation Modelling Practice and Theory 19 (2011) 1021–1034.
  22. Bruce Hendrickson, Karen Devine, Dynamic load balancing in computational mechanics, Computer methods in applied mechanics and engineering 184 (2000) 485-500.
  23. Mark Baker, Rajkumar Buyya, and Domenico Laforenza, Grids and Grid technologies for wide-area distributed computing, Software practice and experience 2002; (DOI: 10. 1002/spe. 488)
  24. Sara Kardani-Moghaddam, Farzad Khodadadi, Reza Entezari-Maleki, Ali Movaghar, A Hybrid Genetic Algorithm and Variable Neighborhood Search for Task Scheduling Problem in Grid Environment, Engineering 00 (2011) 3808-3814.
  25. Zhongju Zhang, Weiguo Fan, Web server load balancing: A queueing analysis, European Journal of Operational Research 186 (2008) 681–693.
  26. Jiannong Cao, Graeme Bennett, Kang Zhang, Direct execution simulation of load balancing algorithms with real workload distribution, The Journal of Systems and Software 54 (2000) 227-237.
  27. Vladimir V. Korkhov, Jakub T. Moscicki, Valeria V. Krzhizhanovskay, Dynamic workload balancing of parallel applications with user-level scheduling on the Grid, Future Generation Computer Systems 25 (2009) 28–34.
  28. Ka-Po Chow and Yu-Kwong Kwok, On Load Balancing for Distributed Multiagent Computing, IEEE Transactions on parallel and distributed systems, Vol. 13, No. 8, Aug. (2002) 787-801.
  29. Wang Lei, Chen Qing, Gao Zhanjun, Power Systems Fault Diagnosis Based On Grid Computing, The International Conference on Advanced Power System Automation and Protection, IEEE (2011) 1557-1561.
  30. Ruchir Shah, Bhardwaj Veeravalli, and Manoj Misra, On the Design of Adaptive and Decentralized Load-Balancing Algorithms with Load Estimation for Computational Grid Environments, IEEE Transactions on parallel and distributed systems, Vol. 18, No. 12, Dec. (2007) 1675-1686.
  31. Alpana Rajan, Anil Rawat, Rajesh Kumar Verma, Virtual Computing Grid using Resource Pooling, International Conference on Information Technology, IEEE (2008) 59-64.
  32. Nirmalya Roy, and Sajal K. Das, Enhancing Availability of Grid Computational Services to Ubiquitous Computing Applications, IEEE Transactions on parallel and distributed systems, Vol. 20, No. 7, July (2009) 953-967.
  33. S. Luo, X. Peng, S. Fan, P. Zhang, Study on Computing Grid Distributed Middleware and Its Application, International Forum on Information Technology and Applications, IEEE (2009) 441-445.
  34. M. Ali, Z. Y. Dong, and P. Zhang, Adoptability of grid computing technology in power systems analysis, operations and control, IET Generation, Transmission & Distribution, Vol. 3, Iss. 10 (2009) 949-959.
  35. Kuo-Chan Huang, On Effects of Resource Fragmentation on Job Scheduling Performance in Computing Grids, 10th International Symposium on Pervasive Systems, Algorithms, and Networks, IEEE (2009) 701-705.
  36. Lizhe Wang, G. V. Laszewski, Dan Chen, Jie Tao, and M. Kunze, Provide Virtual Machine Information for Grid Computing, IEEE Transactions on systems, man, and cybernetics-part a: Systemand Humans, Vol. 40, No. 6, Nov. (2010) 1362-1374.
  37. P. G. S. Tiburcio, M. A. Spohn, ad hoc Grid: An Adaptive and Self-Organizing Peer-to-Peer Computing Grid, 10th International Conference on Computer and Information Technology (CIT) IEEE (2010) 225-232.
  38. Liang Bai, Yan-Li Hu, Song-Yang Lao, Wei-Ming Zhang, Task Scheduling with Load Balancing using Multiple Ant Colonies Optimization in Grid Computing, Sixth International Conference on Natural Computation (ICNC), IEEE (2010) 2715-2719.
  39. Y. Murata, R. Egawa, M. Higashida, H. Kobayashi, A History-Based Job Scheduling Mechanism for the Vector Computing Cloud, 10th Annual International Symposium on Applications and the Internet, IEEE (2010) 125-128.
  40. Alexandru Iosup and Dick Epema, Grid Computing Workloads, IEEE Internet Workloads March/April (2011) 19-26.
  41. Shuai Zhang, Shufen Zhang, The Comparison Between Cloud Computing and Grid Computing, International Conference on Computer Application and System Modeling (ICCASM), IEEE (2010) 72-75.
  42. Rajkumar Rajavel, De-Centralized Load Balancing for the Computational Grid Environment, Proceedings of the International Conference on Communication and Computational Intelligence, India (2010) 419-424.
  43. K. Hasham, A. D. Peris, A. Anjum, D. Evans, S. Gowdy, J. M. Hernandez, E. Huedo, D. Hufnagel, F. van Lingen, R. McClatchey, and S. Metson, CMS Workflow Execution Using Intelligent Job Scheduling and Data Access Strategies, IEEE Tranasaction on nuclear science, Vol. 58, No. 3, June (2011) 1221-1232.
  44. Naidila Sadashiv, S. M Dilip Kumar, Cluster, Grid and Cloud Computing: A Detailed Comparison, The 6th International Conference on Computer Science & Education (ICCSE), IEEE Aug. (2011) 477-482.
  45. Jang Uk In, Soocheol Lee, Seungmin Rho, and Jong Hyuk Park, Policy-Based Scheduling and Resource Allocation for Multimedia Communication on Grid Computing Environment, IEEE Systems journal, Vol. 5, No. 4, Dec. (2011) 451-459.
  46. W. Cheng, J. Congfeng, Liu Xiaohu, Fuzzy Logic-Based Secure and Fault Tolerant Job Scheduling in Grid, Tsinghua Science and Technology, Vol. 12 N0. S1 (2007) 45-50.
  47. Malcolm Irving, Gareth Taylor, and Peter Hobson, Plug in to Grid Computing Moving Beyond the Web, IEEE power & energy magazine, March/April (2004) 40-44.
  48. G. Manimaran, M. Shashidhar, Anand Manikutty, C. Siva Ram Murthy, Integrated Scheduling of Tasks and Messages in Distributed Real-time Systems, IEEE (1997) 64-71.
  49. Angelo Boccia, Gianluca Busiello, Luciano Milanesi, and Giovanni Paolella, A Fast Job Scheduling System for a Wide Range of Bioinformatic Applications, IEEE Transactions on Nanobioscience, Vol. 6, No. 2, June (2007) 149-154.
  50. M. Ali, Z. Y. Dong, X. Li, and P. Zhang, RSA-Grid: A Grid Computing based Framework for Power System Reliability and Security Analysis, IEEE (2006) 1-7.
  51. Zeng Zeng,and Bharadwaj Veeravalli, Design and Performance Evaluation of Queue-and-Rate-Adjustment Dynamic Load Balancing Policies for Distributed Networks, IEEE Transactions on Computers, Vol. 55, No. 11, Nov. 2006) 1410-1422.
  52. Globus, http://www. globus. org, accessed March 2013.
  53. NetSolve/GridSolve, http://icl. cs. utk. edu/netsolve, 2013.
  54. EGI - European Grid Infrastructure, http://www. egi. eu/about/egi-inspire//, 2013
  55. Cactus, http://cactuscode. org, 2013.
  56. Legion: A Worldwide Virtual Computer, http://legion. virginia. edu, accessed Jan. 2013.
  57. UNICORE-Distributed computing and data resources, http://www. unicore. eu, accessed Jan. 2013.
  58. Condor-High Throughput Computing, http://research. cs. wisc. edu/htcondor/, 2013.
  59. Grid Simulation Toolkit , http://www. cloudbus. org/gridsim/, 2013.
Index Terms

Computer Science
Information Sciences

Keywords

Survey Grid Computing Load Balancing Scheduling Job distribution Performance evaluation