Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32131
An Agent Based Dynamic Resource Scheduling Model with FCFS-Job Grouping Strategy in Grid Computing

Authors: Raksha Sharma, Vishnu Kant Soni, Manoj Kumar Mishra, Prachet Bhuyan, Utpal Chandra Dey


Grid computing is a group of clusters connected over high-speed networks that involves coordinating and sharing computational power, data storage and network resources operating across dynamic and geographically dispersed locations. Resource management and job scheduling are critical tasks in grid computing. Resource selection becomes challenging due to heterogeneity and dynamic availability of resources. Job scheduling is a NP-complete problem and different heuristics may be used to reach an optimal or near optimal solution. This paper proposes a model for resource and job scheduling in dynamic grid environment. The main focus is to maximize the resource utilization and minimize processing time of jobs. Grid resource selection strategy is based on Max Heap Tree (MHT) that best suits for large scale application and root node of MHT is selected for job submission. Job grouping concept is used to maximize resource utilization for scheduling of jobs in grid computing. Proposed resource selection model and job grouping concept are used to enhance scalability, robustness, efficiency and load balancing ability of the grid.

Keywords: Agent, Grid Computing, Job Grouping, Max Heap Tree (MHT), Resource Scheduling.

Digital Object Identifier (DOI):

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1890


[1] Foster, and C. Kesselman, Globus: a metacomputing infrastructure toolkit, International Journal of High Performance Computing Applications, Vol. 2, pp. 115-128, 1997.
[2] F. Dong and S. G. Akl, Scheduling algorithm for grid computing: state of the art and open problems, Technical Report of the Open Issues in Grid Scheduling Workshop, School of Computing, University Kingston, Ontario, January, 2006.
[3] Rajkumar, Buyya: Architecture Alternatives for Single System ImageClusters, Conference on High Performance Computing on Hewlett- Packard Systems (HiPer'99), Tromse, Norway, 1999.
[4] Fufang Li, Deyu Qi, Limin Zhang, Xianguange Zhang and Zhilli Zhang, "Research on Novel Dynamic Resource Management and Job Scheduling in Grid Computing", Proceedings of the IEEE first International Multi-Symposiums on Computer and Computational Science, IEEE, 2006.
[5] Ms.P.Muthuchelvi, Dr.V.Ramachandran, "ABRMAS: Agent Based Resource Management with Alternate Solution", The Sixth International Conference on Grid and Cooperative Computing IEEE, 2007.
[6] Junyan Wang, Yuebin Xu, Guanfeng Liu, Zhenkuan Pan, and Yongsheng Hao, "New Resource Discovery Mechanism with Negotiate Solution Based on Agent in Grid Environments", The 3rd International Conference on Grid and Pervasive Computing, Workshops, IEEE, 2008.
[7] Homer Wu,Chong-Yen Lee,Wuu-Yee chen,Tsang Lee, "A Job schedule Model Based on Grid Environment", Proceeding of the First International Conference on Complex, Intelligent and Software Intensive System, IEEE, 2007.
[8] Nithiapidary Muthuvelu, Junyang Liu, "A Dynamic Job Grouping- Based Scheduling for Deploying Application with Fine-Grained tasks on Global Grids", Vol. 44, Australasian Workshop on Grid Computing and e-Research, AusGrid -2005.
[9] Quan Liu, Yeqing Liao, "Grouping based Fine-Grained job Scheduling in Grid Computing", First International Workshop on Education Technology and Computer Science, Vol.1,pp. 556-559, IEEE, 2009.
[10] Ng Wai Keat, Ang Tan Fong, Ling Teck Chaw, Liew Chee Sun, "Scheduling Framework For Bandwidth-Aware Job Grouping-Based Scheduling In Grid Computing", Vol.19(2), pp. 117-126, Malaysian Journal of Computer Science, 2006.
[11] J. Santoso, G.D. van Albada, B.A.A. Nazief, P.M.A. Sloot, "Hierarchical Job Scheduling for Clusters of Workstations", pp. 99- 105. ASCI, June 2000.
[12] R. Buyya and M. Murshed, GridSim; A toolkit for the modeling and simulation of distributed management and scheduling for grid computing, 2002