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| 基于遗传算法的网络资源配置优化 | |
| 引用本文： | 张英,杨雅辉,田浩然,张威,董晶晶. 基于遗传算法的网络资源配置优化[J]. 计算机科学, 2012, 39(5): 36-39 |
| 作者姓名： | 张英 杨雅辉 田浩然 张威 董晶晶 |
| 作者单位： | 1. 中国科学院计算技术研究所 北京100190;北京大学软件与微电子学院 北京102600 2. 北京大学软件与微电子学院 北京102600 3. 中国矿业大学(北京)机电与信息工程学院 北京100083 |
| 摘 要： | 随着新一代网络的结构复杂化和应用多样化,如何进一步提高实时业务的服务质量,是急需解决的重要问题之一,而合理配置和优化网络资源是解决该问题的有效方法。针对多业务网络,提出一种以网络资源均衡度为目标、QoS为约束的优化模型;应用改进的遗传算法实现带宽和节点缓冲区资源的优化配置,以实现网络流量分布均衡,从而提高网络性能。通过分析遗传算法种群适应度的变化趋势,给出一种基于种群稳定性系数阈值的迭代终止方法,以提高算法收敛效率。通过实验验证了以上方法的有效性。 |
| 关 键 词： | 多业务网络 资源配置优化 遗传算法 |
Optimization of Network Resource Allocation Based on Genetic Algorithm |
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| ZHANG Ying , YANG Ya-hui , TIAN Hao-ran , ZHANG Wei , DONG Jing-jing. Optimization of Network Resource Allocation Based on Genetic Algorithm[J]. Computer Science, 2012, 39(5): 36-39 | |
| Authors: | ZHANG Ying YANG Ya-hui TIAN Hao-ran ZHANG Wei DONG Jing-jing |
| Affiliation: | 3(The Institute of Computing Technology,the Chinese Academy of Sciences,Beijing 100190,China)1(School of Software and Microelectronics,Peking University,Beijing 102600,China)2(School of Mechanical Electronic & Information Engineering,China University of Mining & Technology,Beijing 100083,China)3 |
| Abstract: | As the next-generation network architecture becomes more and more complex and the applications become more diverse, how to improve the performance of the network becomes a big problem that we must solve. One important effective method to solve the problem is to rationally allocate and optimize the network resource. Based on the multiservice networks, this paper proposed a new optimization model which is targeted at network resource leveling under the QoS restrictions,and balance of network traffic distribution by optimizing the allocation of the network bandwidth and buffers with an improved genetic algorithm so as to improve the performance of network. A method based on threshold of population stability coefficient to terminate the iteration of the genetic algorithm was given by analysing the variation trend of population stability coefficient. The experiments show that the method is effective to improve the efficiency of the algorithm. |
| Keywords: | Multiservice network Optimization of allocation of network resource Uenetic algorithm |
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