Name
Abstract | ||
|---|---|---|
To execute large scale applications exploiting the unemployed aggregated power available on grid nodes, effective and efficient mapping algorithms must be designed. Since the problem of optimally mapping is NP--complete, heuristic techniques can be profitably adopted to find near--optimal solutions. Here a multiobjective Differential Evolution algorithm is implemented and tested on different mapping scenarios with the aim to fulfill several optimization criteria. The results attained show the robustness of the evolutionary approach proposed in dealing with multisite grid mapping. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1145/1555284.1555289 | BADS '09 Proceedings of the 2009 workshop on Bio-inspired algorithms for distributed systems |
Keywords | Field | DocType |
multiobjective differential evolution algorithm,computational grids,grid node,multisite mapping,large scale application,differential evolution,different mapping scenario,optimally mapping,evolutionary approach,multisite grid mapping,optimal solution,heuristic technique,innovative perspective,multiobjective optimization,efficient mapping algorithm,profitability | Heuristic,Mathematical optimization,Computer science,Differential evolution,Multi-objective optimization,Robustness (computer science),Mapping algorithm,Grid,Differential evolution algorithm | Conference |
Citations | PageRank | References |
0 | 0.34 | 24 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ivanoe De Falco | 1 | 242 | 34.58 |
| D. Maisto | 2 | 146 | 11.20 |
| Umberto Scafuri | 3 | 116 | 16.33 |
| Ernesto Tarantino | 4 | 361 | 42.45 |
| Antonio Della Cioppa | 5 | 141 | 20.70 |