Numerical Recipes in C: The Art of Scientific Computing
Numerical Recipes in C: The Art of Scientific Computing
The Anatomy of the Grid: Enabling Scalable Virtual Organizations
Euro-Par '01 Proceedings of the 7th International Euro-Par Conference Manchester on Parallel Processing
Self-Adaptive and Self-Optimising Resource Monitoring for Dynamic Grid Environments
DEXA '04 Proceedings of the Database and Expert Systems Applications, 15th International Workshop
A framework for adaptive execution in grids
Software—Practice & Experience
Self adaptivity in Grid computing: Research Articles
Concurrency and Computation: Practice & Experience - Grid Performance
Theory of Self-Reproducing Automata
Theory of Self-Reproducing Automata
Self-adaptive applications on the grid
Proceedings of the 12th ACM SIGPLAN symposium on Principles and practice of parallel programming
On the Origin of Grid Species: The Living Application
ICCS '09 Proceedings of the 9th International Conference on Computational Science: Part I
A survey of self-adaptive grids
IEEE Communications Magazine
Self-adaptive deployment of parametric sweep applications through a complex networks perspective
ICCSA'11 Proceedings of the 2011 international conference on Computational science and its applications - Volume Part II
ACRI'06 Proceedings of the 7th international conference on Cellular Automata for Research and Industry
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Grid computing infrastructures are systems composed by an heterogeneous and geographically distributed resource set. Despite the advantages of such paradigm, several challenges related to grid resources selection and resources availability still demand active research. The aim of this article is to provide an efficient and self-adaptive resources selection strategy for grid applications deployment. This resources adaptation capability is provided by applying nature-inspired algorithms during the selection process. Specifically, both the preferential attachment technique from Complex Network field and a cellular automata model are used. Finally, the results obtained during tests in a real grid show that the proposed model achieves an effective use of grid resources, resulting in a reduction of application execution time and in an increased rate of successfully finished tasks. In conclusion, the model improves the infrastructure throughput for grid applications.