Allocating Independent Subtasks on Parallel Processors
IEEE Transactions on Software Engineering
Guided self-scheduling: A practical scheduling scheme for parallel supercomputers
IEEE Transactions on Computers
Communications of the ACM
Factoring: a method for scheduling parallel loops
Communications of the ACM
Data mining: concepts and techniques
Data mining: concepts and techniques
A Novel Data Distribution Technique for Host-Client Type Parallel Applications
IEEE Transactions on Parallel and Distributed Systems
A grid-enabled MPI: message passing in heterogeneous distributed computing systems
SC '98 Proceedings of the 1998 ACM/IEEE conference on Supercomputing
Scheduling Divisible Loads in Parallel and Distributed Systems
Scheduling Divisible Loads in Parallel and Distributed Systems
Parallel and Distributed Association Mining: A Survey
IEEE Concurrency
Parallel Mining of Association Rules
IEEE Transactions on Knowledge and Data Engineering
Trapezoid Self-Scheduling: A Practical Scheduling Scheme for Parallel Compilers
IEEE Transactions on Parallel and Distributed Systems
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
A Class of Loop Self-Scheduling for Heterogeneous Clusters
CLUSTER '01 Proceedings of the 3rd IEEE International Conference on Cluster Computing
Scheduling Strategies for Master-Slave Tasking on Heterogeneous Processor Platforms
IEEE Transactions on Parallel and Distributed Systems
Scheduling Divisible Loads on Star and Tree Networks: Results and Open Problems
IEEE Transactions on Parallel and Distributed Systems
Overhead Analysis of a Dynamic Load Balancing Library for Cluster Computing
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 1 - Volume 02
The Anatomy of the Grid: Enabling Scalable Virtual Organizations
International Journal of High Performance Computing Applications
An Enhanced Parallel Loop Self-Scheduling Scheme for Cluster Environments
The Journal of Supercomputing
Distributed loop-scheduling schemes for heterogeneous computer systems: Research Articles
Concurrency and Computation: Practice & Experience
A Convergence Study of the Discrete FGDLS Algorithm
IEICE - Transactions on Information and Systems
Locality and Loop Scheduling on NUMA Multiprocessors
ICPP '93 Proceedings of the 1993 International Conference on Parallel Processing - Volume 02
Introduction to grid computing with globus
Introduction to grid computing with globus
Loosely-coupled loop scheduling in computational grids
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
A performance-based parallel loop self-scheduling on grid computing environments
NPC'05 Proceedings of the 2005 IFIP international conference on Network and Parallel Computing
A hybrid parallel loop scheduling scheme on grid environments
GCC'05 Proceedings of the 4th international conference on Grid and Cooperative Computing
On optimum multi-installment divisible load processing in heterogeneous distributed systems
Euro-Par'05 Proceedings of the 11th international Euro-Par conference on Parallel Processing
GPC'06 Proceedings of the First international conference on Advances in Grid and Pervasive Computing
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Imbalanced workload-distribution can significantly degrade performance of grid computing environments. In the past, the theory of divisible load has been widely investigated in static heterogeneous systems. However, it has not been widely applied to grid environments, which are characterized by heterogeneous resources and dynamic environments. In this paper, we propose a performance-based approach to workload distribution for master-slave types of applications on grids. Furthermore, applications with irregular workloads are addressed. We implemented three kinds of applications and conducted experimentations on our grid test-beds. Experimental results show that this approach performs more efficiently than conventional schemes. Consequently, we claim that dynamic workload distribution can benefit applications on grid environments.