遗传蚁群算法在云计算资源调度中的应用

Application of genetic ant colony algorithm in cloud computing resource scheduling

针对现有云计算资源调度算法收敛速度慢、求精解效率低等问题,有机结合遗传算法的全局搜索能力快和蚁群算法的正反馈收敛求解效率高的特点,提出一种资源调度算法。采用遗传算子生成初始信息素分布,在此基础上,通过双向收敛蚁群算子求出精确解。实验结果表明,该算法在求解精度和收敛速度方面具有优越性,是一种有效的云计算资源调度算法。

For the slow convergence and low refinement efficiency of existing cloud computing cloud resource scheduling algo-rithms ,a resource scheduling algorithm was proposed combining fast global search ability of genetic algorithm and positive feed-back mechanism of convergence ant colony algorithm respectively. The initial pheromone distribution was generated using genetic algorithm, and based on this distribution, exact solutions were derived using two-way convergence ant colony. Experimental re-sults show that the algorithm has advantages on convergence speed and refinement efficiency, and it is an effective cloud resource scheduling algorithm.