A Dynamic Knowledge-Based Task Scheduling Algorithm in Simulation Grid Environment

Simulation grid is a specific grid which is based on general grid technology and oriented towards simulation. At present, researches on simulation grid are still at the fledgling stage. Simulation resources as well as federates in HLA-based distributed simulation are statically bound now. Introduction of grid technology makes the dynamic allocation of the simulation resources come to reality. However，there is little relevant literature discussing task scheduling in simulation grid now. Therefore, it's a new research field of high practical value. Simulation grid provides a flexible and powerful simulation platform to execute large-scale simulation applications. The focus here is on the task scheduling in simulation grid environment. In this paper, a new task scheduling model in simulation grid is built firstly, and a novel knowledge-based dynamic task scheduling algorithm KMO is proposed for scheduling N independent tasks with the different length onto a simulation gird with M resources whose computing power varies over time. In this algorithm, the results of several scheduling are collected and refined to form knowledge, which is then used in pretreatment stage in the algorithm. Finally, the experiment result shows that KMO is better than the traditional task scheduling algorithms in simulation grid environment.