Grid Load Balancing Scheduling Algorithm Based on Statistics Thinking

As grid technologies evolve quickly on Internet, research related to resource allocation and task scheduling faces new opportunities and challenges. These new technologies, ideas and approaches provide a new environment for researching and developing load balancing-oriented job scheduling system. Aiming at the hierarchical grid model structure, following statistical thinking, this paper proposed a new task scheduling and resource allocation algorithm, which can not only increase the utilization of resources and system throughput, but also realize the load balancing within grid systems. This algorithm consists of three main modules, they are load tracking module, job distributing module and load monitoring module. On the basis of having explained the functions of the different functional parts and the relationships between them, the corresponding pseudo-code algorithm are given. The results of simulative experiments show that the algorithm is effective.