摘要
任务调度是一个NP-hard问题,而且是并行与分布式计算中一个必不可少的组成部分,特别是在网格计算环境中任务调度更加复杂。结合免疫克隆算法和模拟退火算法的优点,提出了一种网格任务调度优化模型和算法。仿真实验结果表明,这种调度算法有效地实现了资源的负载均衡,克服了遗传算法容易陷入局部最优的缺点,可以成功地应用于网格任务调度中。
Task scheduling is a NP-hard problem and also an integral part of parallel and distributed computing. It becomes more complicated especially in the grid computing environment. An optimal task scheduling model and an algorithm were brought forward, which combined the advantages of immune elonal algorithm and simulated annealing. The simulation results show that this algorithm achieves resource load balancing, and it overcomes the shortcomings of genetic algorithm, and can be applied to the optimization of task scheduling successfully.
出处
《计算机应用》
CSCD
北大核心
2008年第11期2867-2870,共4页
journal of Computer Applications
关键词
网格计算
任务调度
免疫克隆算法
模拟退火算法
并行模拟退火克隆算法
grid computing
task scheduling
immune clonal algorithm
simulated annealing algorithm
parallel simulated annealing clonal algorithm
