ACOCS:一种云环境下资源调度混合算法

蚁群算法在优化组合问题中有着重要的意义,传统的蚁群调度算法搜索速度慢、容易陷入局部最优。针对这种情况,结合布谷鸟搜索算法,提出一种基于蚁群算法与布谷鸟搜索算法的混合算法(ACOCS),用于云环境下的资源调度。该方法有效保留了蚁群算法求解精度高和鲁棒性的特性,并融入了布谷鸟搜索具有快速全局搜索能力的优势。仿真实验结果表明,提出的ACOCS调度算法有效减少了调度所需的响应时间,也在一定程度上提高了系统资源利用率。

ACOCS : A hybrid resource scheduling algorithm in cloud environment

The ant colony algorithm has great significance in solving composition optimization problems. However, the traditional ant colony scheduling algorithm has some drawbacks such as slow searching speed and easy to fall into local optimum. In view of this situation, combining the ant colony algorithm with the cuckoo search algorithm, we propose a hybrid algorithm (ACOCS) for resource scheduling in cloud environment. This method not only effectively preserves the high accuracy and robustness of the ant colony algorithm , but also integrates the rapid global search capability feature of the cuckoo search algorithm . Simulation results show that the proposed ACOCS scheduling strategy is better than the ant colony algorithm. It not only reduces the response time required for effective scheduling, but also improves the system resource utilization to some extent.