Framework for Peer-to-Peer Distributed Computing in a Heterogeneous, Decentralized Environment
GRID '02 Proceedings of the Third International Workshop on Grid Computing
Performance control of scientific coupled models in Grid environments: Research Articles
Concurrency and Computation: Practice & Experience - Grid Performance
Self adaptivity in Grid computing: Research Articles
Concurrency and Computation: Practice & Experience - Grid Performance
The Anatomy of the Grid: Enabling Scalable Virtual Organizations
International Journal of High Performance Computing Applications
The Cactus Worm: Experiments with Dynamic Resource Discovery and Allocation in a Grid Environment
International Journal of High Performance Computing Applications
A New Algorithm for Finding Minimal Sample Uniques for Use in Statistical Disclosure Assessment
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
A distributed dynamic aspect machine for scientific software development
Proceedings of the 1st workshop on Virtual machines and intermediate languages for emerging modularization mechanisms
Hi-index | 0.00 |
A framework is proposed that dynamically adapts to resource changes in a distributed heterogeneous environment. In this framework, computational tasks are wrapped into autonomous entities which are able to control themselves locally. Global control is provided in a decentralised manner via control units which link with these local entities in hierarchies, monitor them and coordinate their behaviour. With these mechanisms, the framework controls performance of a distributed application in a heterogeneous environment by adjusting load balance and adapting to resource changes. Fault tolerance is provided, being viewed as a special case of performance loss. Mixed strategies are applied, including global and local control policies, and their benefits are illustrated in terms of scalability and efficiency.