BLOMERS: Balanced Load Multi-Constrained Resource Scheduler

The process of resource management in local and wide-area distributed systems involves three main phases: resource discovery, resource scheduling and resource allocation. This paper presents a heuristic resource scheduler to cover the scheduling phase in large-scale distributed systems such as Grids. This approach is supported by BLOMERS (balanced load multi-constrain resource scheduler). Our heuristic scheduler implements a Genetic Algorithm (GA) in order to improve the scalability of the system, in large-scale Grids the amount of resource is massive but their computational capacity is low. Therefore, selection of computational resources to allocate customers services becomes an NP-hard problem. The paper outlines a performance evaluation by means of experimental tests. The results highlight two aspects: The scheduling system is reliable in real large-scale Grids and BLOMERS heuristic scheduler offers better performance than common selection algorithms when the number of resource requests is increasing.