An Agent Based Dynamic Resource Scheduling Model with FCFS-Job Grouping Strategy in Grid Computing
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.
[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
[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
@article{"International Journal of Information, Control and Computer Sciences:56105", author = "Raksha Sharma and Vishnu Kant Soni and Manoj Kumar Mishra and Prachet Bhuyan and Utpal Chandra Dey", title = "An Agent Based Dynamic Resource Scheduling Model with FCFS-Job Grouping Strategy in Grid Computing", abstract = "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.", volume = "4", number = "4", pages = "728-5", }