融合小生境遗传禁忌的多目标网格调度研究

Multi-objective grid task scheduling algorithms based on combined strate-gy of Niche genetic algorithm and Tabu search

针对在动态、复杂的网格系统中,资源的失效非常频繁,影响网格计算的服务质量和效率的问题,提出了基于融合小生境的遗传禁忌的多目标网格任务调度算法,将任务生存性和任务完成时间(Makespan)结合起来,给出一个可调节的多目标集成效用函数,实现了基于融合小生境的遗传禁忌的多目标启发式调度算法。模拟实验结果表明,该算法能够有效地平衡任务生存性和Makespan两个目标,更适合开放复杂的网格计算环境。

Combining the advantage of genetic algorithm and tabu search,a combined evolutionary computing is proposed to optimize the grid task scheduling strategy.In the complex and dynamic grid system,failure of resources is very common.To mitigate this problem,a local objective function which can be adjusted is proposed by incorporating the makespan and the survivability of task.The simulation results show that the scheduling algorithm can trade off these two objectives.So it can be applied in the complex grid computing environment well