摘要
根据拍卖机制的在线信誉网格资源管理模型,设计基于遗传算法的网格作业全局调度策略。引入时间和花费2个经济因素,改进遗传算法的收敛性。改进算法根据用户需求得到最优化的资源分派策略,提高网格系统的总体性能。将该算法纳入GridSim模拟器进行系统测试,结果证明其优于传统调度算法。
According to an online reputation grid resource management model of auction mechanism, this paper designs the global scheduling strategy of grid jobs based on the Genetic Algorithm(GA). It introduces two economy factors which are time and cost, and improves GA's astringency. The improved algorithm can achieves the optimized resource allocation strategy on user demand, and improves the system's performance. This algorithm is tested on the GridSim simulator, and the results prove that it is better than traditional algorithms.
出处
《计算机工程》
CAS
CSCD
北大核心
2009年第9期187-189,共3页
Computer Engineering
基金
山西省青年自然科学基金资助项目(2008021025)