Authors:
Arturo Pérez-Cebreros
;
Gilberto Martínez-Luna
and
Nareli Cruz-Cortés
Affiliation:
National Polytechnic Institute, Mexico
Keyword(s):
Particle Swarm Optimization, Genetic Algorithms, Grid, Database, Query Scheduler.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence and Decision Support Systems
;
Databases and Information Systems Integration
;
Enterprise Information Systems
;
Enterprise Resource Planning
;
Enterprise Software Technologies
;
Evolutionary Programming
;
Object-Oriented Database Systems
;
Simulation and Modeling
;
Simulation Tools and Platforms
;
Software Engineering
Abstract:
The accelerated development in Grid computing has positioned it as promising next generation computing platforms. Grid computing contains resource management, task scheduling, security problems, information management and so on. In the context of database query processing, existing parallelisation techniques can not operate well in Grid environments, because the way they select machines and allocate queries. This is due to the geographic distribution of resources that are owned by different organizations. The resource owners have different usage or access policies, cost models, varying loads and availability. It is a big challenge for efficient scheduling algorithm design and implementation. In this paper, a heuristic approach based on particle swarm optimization algorithm is adopted to solving parallel query scheduling problem in grid environment.