An Improved Ant Colony Algorithm for Agricultural Knowledge Storage Scheduling Under Grid Environment - Computer Vision Research Group（计算机视觉实验室）

Distributed knowledge resources management is one of the key technologies for the development of grid computing as well as cloud computing. In this paper, an improved Ant Colony Algorithm is proposed to apply to agriculture knowledge resources scheduling under grid environment. Instead of the random and uncertain of grid nodes distances under Ant Colony Algorithm, the improved Ant Colony Algorithm expressed the distances of grid nodes directly using two-dimensional coordinate system according to the semantic distances of domain concepts. The distances of different kinds of agriculture knowledge resources can be calculated visualized. The efficiency of grid storage scheduling process can be improved normally more than 5 times comparing to the traditional Ant Colony Algorithm.