基于粒子群优化算法的Hadoop调度算法研究

为提高Hadoop平台性能,提出一种基于粒子群优化算法的Hadoop调度算法。以粒子位置代表可行的资源调度方案,以任务完成时间及资源负载均衡度作为目标函数,通过粒子群优化算法,找到最优的资源调度方案。实验结果表明,该算法能够很好的平衡资源负载,减少任务完成时间,有效的提高了Hadoop平台的性能。

Research of scheduling algorithm for Hadoop based on particle swarm optimization

In order to improve the performance of Hadoop, the paper proposed a new scheduling algorithm based on particle swarm optimization. In this paper, the position of particles represent feasible resource scheduling scheme, the cloud computing task completion time and resource load balancing were taken as the objective function, the optimal resource scheduling scheme was obtained by the particle swarm optimization algorithm. The experimental results show that this algorithm can well balanced resource load and reduce the task completion time and effectively improve the performance of the Hadoop platform.