基于蚁群模拟退火的云任务调度算法改进

Improved Algorithm of Cloud Task Scheduling Based on Ant Colony Simulated Annealing

云计算的高速发展使如何提升云任务调度成为一项新的研究课题。任务调度属于NP优化问题,部分超启发计算方式能够应用于任务调度问题中。蚁群算法在云调度中显现出较为明显的问题,因此,将蚁群算法与模拟退火算法结合,可以形成一种新型蚁群模拟退火算法,能够解决云计算中存在调度问题,能够在较短时间内均衡资源负荷,实现结构优化。

With the rapid development of cloud computing, how to improve cloud task scheduling has become a new research topic. Task scheduling is a NP optimization problem, and partial hyper heuristics can be applied to task scheduling problems. Ant colony algorithm shows more obvious problems in cloud scheduling. So the combination of ant colony algorithm and simulated annealing algorithm can form a new ant colony simulated annealing algorithm, which can solve the scheduling problem in cloud computing, and can balance the resource load in a relatively short time to achieve structural optimization.