| 基于改进免疫遗传算法的网格任务调度 |
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| 引用本文： | 张京军,刘文娟,刘光远. 基于改进免疫遗传算法的网格任务调度[J]. 河北工程大学学报(自然科学版), 2013, 30(2): 80-83 |
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| 作者姓名： | 张京军 刘文娟 刘光远 |
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| 作者单位： | 河北工程大学信息与电气工程学院,河北邯郸,056038 |
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| 基金项目： | 河北省自然科学基金资助项目“基于粗粒度并行遗传算法的网格任务调度研究” |
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| 摘 要： | 为改进网格计算中任务调度的低效问题,采用十进制的实数编码规则产生初始抗体群,由免疫遗传算法经过克隆和变异算子生成资源集合中的蚁群信息素,进而利用蚁群算法的并行性展开全局搜索,通过CloudSim仿真平台进行模拟,与粒子群算法及蚁群遗传算法进行对比,结果表明,改进的免疫遗传算法能够大幅提高网格计算任务调度效率,有效地解决网格任务调度问题.
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| 关 键 词： | 网格计算 免疫遗传算法 任务调度 蚁群算法 |
| 收稿时间： | 2013-01-21 |
Task scheduling in grid computing based on improved immune genetic algorithm |
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| ZHANG Jing-jun,LIU Wen-juan and LIU Guang-yuan. Task scheduling in grid computing based on improved immune genetic algorithm[J]. Journal of Hebei University of Engineering(Natural Science Edition), 2013, 30(2): 80-83 |
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| Authors: | ZHANG Jing-jun LIU Wen-juan LIU Guang-yuan |
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| Affiliation: | School of Information and Electrical Engineering, Hebei University of Engineering, Hebei Handan 056038, China;School of Information and Electrical Engineering, Hebei University of Engineering, Hebei Handan 056038, China;School of Information and Electrical Engineering, Hebei University of Engineering, Hebei Handan 056038, China |
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| Abstract: | For the inefficient of the current grid computing, the decimal real number encoding rules was chosen to generate the initial antibody group, first use the immune genetic algorithm to generate the initial pheromone distribution in the collection, then use the parallelism of the ant colony algorithm for global search, finally using CloudSim as a simulation platform to simulate, compared with the particle swarm optimization (pso) and ant colony genetic algorithm, results indicate that the Improved Immune Genetic Algorithm can provide efficient task scheduling strategy and it can solve the problem more effectively. |
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| Keywords: | grid computing immune genetic algorithm task scheduling colony optimization |
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