Improving job scheduling algorithms in a grid environment

Due to the advances in human civilization, problems in science and engineering are becoming more complicated than ever before. To solve these complicated problems, grid computing becomes a popular tool. A grid environment collects, integrates, and uses heterogeneous or homogeneous resources scattered around the globe by a high-speed network. A grid environment can be classified into two types: computing grids and data grids. This paper mainly focuses on computing grids. In computing grid, job scheduling is a very important task. A good scheduling algorithm can assign jobs to resources efficiently and can balance the system load. In this paper, we propose a hierarchical framework and a job scheduling algorithm called Hierarchical Load Balanced Algorithm (HLBA) for Grid environment. In our algorithm, we use the system load as a parameter in determining a balance threshold. And the scheduler adapts the balance threshold dynamically when the system load changes. The main contributions of this paper are twofold. First, the scheduling algorithm balances the system load with an adaptive threshold and second, it minimizes the makespan of jobs. Experimental results show that the performance of HLBA is better than those of other algorithms.