Name
Abstract | ||
|---|---|---|
Grid systems, constituted by multisite andmulti-owner timeshared resources, make a great amount of locally unemployed computational power accessible to users. To profitably exploit this power for processing computationally intensive grid applications, an efficient multisite mapping must be conceived. The mapping of cooperating and communicating application subtasks, already known as NP-complete for parallel systems, results even harder in grid computing because the availability and workload of grid resources change dynamically, so evolutionary techniques can be adopted to find near-optimal solutions. In this paper a mapping tool based on a multiobjective Differential Evolution algorithm is presented. The aim is to reduce the execution time of the application by selecting among all the potential solutions the one which minimizes the degree of use of the grid resources and, at the same time, complies with Quality of Service requirements. The proposed mapper is assessed on some artificial problems differing in application sizes and workload constraints. |
Year | Venue | Keywords |
|---|---|---|
2007 | PPAM | grid resources change dynamically,execution time,grid computing,multiobjective evolutionary approach,grid resource,efficient multisite mapping,application size,computationally intensive grid application,grid system,mapping tool,application subtasks,differential evolution,parallel systems,quality of service,time sharing,profitability |
Field | DocType | Volume |
Grid computing,Workload,Computer science,Quality of service,Exploit,Theoretical computer science,Differential evolution,Execution time,Semantic grid,Grid,Distributed computing | Conference | 4967 |
ISSN | ISBN | Citations |
0302-9743 | 3-540-68105-1 | 0 |
PageRank | References | Authors |
0.34 | 14 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ivanoe De Falco | 1 | 242 | 34.58 |
| Antonio Della Cioppa | 2 | 141 | 20.70 |
| Umberto Scafuri | 3 | 116 | 16.33 |
| Ernesto Tarantino | 4 | 361 | 42.45 |