Dynamic Load Balancing Strategy for Grid Computing
Workload and resource management are two essential functions provided at the service level of the grid software infrastructure. To improve the global throughput of these software environments, workloads have to be evenly scheduled among the available resources. To realize this goal several load balancing strategies and algorithms have been proposed. Most strategies were developed in mind, assuming homogeneous set of sites linked with homogeneous and fast networks. However for computational grids we must address main new issues, namely: heterogeneity, scalability and adaptability. In this paper, we propose a layered algorithm which achieve dynamic load balancing in grid computing. Based on a tree model, our algorithm presents the following main features: (i) it is layered; (ii) it supports heterogeneity and scalability; and, (iii) it is totally independent from any physical architecture of a grid.
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climate simulation data: a challenge problem for data grid technologies.
In Proceeding. of 22th parallel computing, volume 29(10), pages 13-35,
1997.
[2] E. Badidi. Architecture and services for load balancing in object
distributed systems. PhD thesis, Faculty of High Studies, University
of Montreal, Mai 2000.
[3] F. Berman, G. Fox, and Y. Hey. Grid Computing: Making the Global
Infrastructure a Reality. Wiley Series in Communications Networking
& Distributed Systems, 2003.
[4] T.L. Casavant and J.G. Kuhl. A taxonomy of scheduling in general
purpose distributed computing systems. IEEE Transactions on Software
Engineering, 14(2):141-153, 1994.
[5] D.L. Eager, E.D. Lazowska, and J. Zahorjan. Adaptive load sharing in
homogeneous distributed systems. In IEEE Trans. on Soft. Eng., volume
12(5), pages 662-675, 1986.
[6] I. Foster and C. Kesselman. Globus: a metacomputing infrastructure
toolkit. Int. Jour. of Super-Computer and High Performance Computing
Applications, 11(2):115-128, 1997.
[7] I. Foster and C. Kesselman. The Grid: Blueprint for a New Computing
Infrastructure. Morgan Kaufmann, 1998.
[8] GridSim. A grid simulation toolkit for resource modelling
and application scheduling for parallel and distributed computing.
www.buyya.com/gridsim/.
[9] M. Houle, A. Symnovis, and D. Wood. Dimension-exchange algorithms
for load balancing on trees. In Proc. of 9th Int. Colloquium on Structural
Information and Communication Complexity, pages 181-196, Andros,
Greece, June 2002.
[10] H.D. Karatza. Job scheduling in heterogeneous distributed systems.
Journal. of Systems and Software, 56:203-212, 1994.
[11] W. Leinberger, G. Karypis, V. Kumar, and R. Biswas. Load balancing
across near-homogeneous multi-resource servers. In 9th Heterogeneous
Computing Workshop, pages 60-71, 2000.
[12] XtremWeb. A global computing experimental platform.
http://www.lri.fr/fedak/XtremWeb/introduction.php3.
[13] C.Z. Xu and F.C.M. Lau. Load Balancing in Parallel Computers: Theory
and Practice. Kluwer, Boston, MA, 1997.
[14] B. Yagoubi. Dynamic load balancing for beowulf clusters. In Proceeding
of the 2005 International Arab Conference On information Technology,
pages 394-401, Israa University, Jordan, December 6th 8th 2005.
[15] M.J. Zaki, W. Li, and S. Parthasarathy. Customized dynamic load
balancing for a network of workstations. In Proc. of the 5th IEEE
Int. Symp. HDPC, pages 282-291, 1996.
[1] E. Deelman A.Chervenak and al. High performance remote access to
climate simulation data: a challenge problem for data grid technologies.
In Proceeding. of 22th parallel computing, volume 29(10), pages 13-35,
1997.
[2] E. Badidi. Architecture and services for load balancing in object
distributed systems. PhD thesis, Faculty of High Studies, University
of Montreal, Mai 2000.
[3] F. Berman, G. Fox, and Y. Hey. Grid Computing: Making the Global
Infrastructure a Reality. Wiley Series in Communications Networking
& Distributed Systems, 2003.
[4] T.L. Casavant and J.G. Kuhl. A taxonomy of scheduling in general
purpose distributed computing systems. IEEE Transactions on Software
Engineering, 14(2):141-153, 1994.
[5] D.L. Eager, E.D. Lazowska, and J. Zahorjan. Adaptive load sharing in
homogeneous distributed systems. In IEEE Trans. on Soft. Eng., volume
12(5), pages 662-675, 1986.
[6] I. Foster and C. Kesselman. Globus: a metacomputing infrastructure
toolkit. Int. Jour. of Super-Computer and High Performance Computing
Applications, 11(2):115-128, 1997.
[7] I. Foster and C. Kesselman. The Grid: Blueprint for a New Computing
Infrastructure. Morgan Kaufmann, 1998.
[8] GridSim. A grid simulation toolkit for resource modelling
and application scheduling for parallel and distributed computing.
www.buyya.com/gridsim/.
[9] M. Houle, A. Symnovis, and D. Wood. Dimension-exchange algorithms
for load balancing on trees. In Proc. of 9th Int. Colloquium on Structural
Information and Communication Complexity, pages 181-196, Andros,
Greece, June 2002.
[10] H.D. Karatza. Job scheduling in heterogeneous distributed systems.
Journal. of Systems and Software, 56:203-212, 1994.
[11] W. Leinberger, G. Karypis, V. Kumar, and R. Biswas. Load balancing
across near-homogeneous multi-resource servers. In 9th Heterogeneous
Computing Workshop, pages 60-71, 2000.
[12] XtremWeb. A global computing experimental platform.
http://www.lri.fr/fedak/XtremWeb/introduction.php3.
[13] C.Z. Xu and F.C.M. Lau. Load Balancing in Parallel Computers: Theory
and Practice. Kluwer, Boston, MA, 1997.
[14] B. Yagoubi. Dynamic load balancing for beowulf clusters. In Proceeding
of the 2005 International Arab Conference On information Technology,
pages 394-401, Israa University, Jordan, December 6th 8th 2005.
[15] M.J. Zaki, W. Li, and S. Parthasarathy. Customized dynamic load
balancing for a network of workstations. In Proc. of the 5th IEEE
Int. Symp. HDPC, pages 282-291, 1996.
@article{"International Journal of Information, Control and Computer Sciences:52125", author = "Belabbas Yagoubi and Yahya Slimani", title = "Dynamic Load Balancing Strategy for Grid Computing", abstract = "Workload and resource management are two essential functions provided at the service level of the grid software infrastructure. To improve the global throughput of these software environments, workloads have to be evenly scheduled among the available resources. To realize this goal several load balancing strategies and algorithms have been proposed. Most strategies were developed in mind, assuming homogeneous set of sites linked with homogeneous and fast networks. However for computational grids we must address main new issues, namely: heterogeneity, scalability and adaptability. In this paper, we propose a layered algorithm which achieve dynamic load balancing in grid computing. Based on a tree model, our algorithm presents the following main features: (i) it is layered; (ii) it supports heterogeneity and scalability; and, (iii) it is totally independent from any physical architecture of a grid.
", keywords = "Grid computing, load balancing, workload, tree based model.", volume = "2", number = "7", pages = "2335-6", }
