首页> 外文期刊>Networks >A hybrid genetic algorithm for the weight setting problem in OSPF/IS-IS routing
【24h】

A hybrid genetic algorithm for the weight setting problem in OSPF/IS-IS routing

机译:OSPF / IS-IS路由中权重设置问题的混合遗传算法

获取原文
获取原文并翻译 | 示例
           

摘要

Intradomain traffic engineering aims to make more efficient use of network resources within an autonomous system. Interior Gateway Protocols such as OSPF (Open Shortest Path First) and IS-IS (Intermediate System-Intermediate System) are commonly used to select the paths along which traffic is routed within an autonomous system. These routing protocols direct traffic based on link weights assigned by the network operator. Each router in the autonomous system computes shortest paths and creates destination tables used to direct each packet to the next router on the path to its final destination. Given a set of traffic demands between origin-destination pairs, the OSPF weight setting problem consists of determining weights to be assigned to the links so as to optimize a cost function, typically associated with a network congestion measure. In this article, we propose a genetic algorithm with a local improvement procedure for the OSPF weight-setting problem. The local improvement procedure makes use of an efficient dynamic shortest path algorithm to recompute shortest paths after the modification of link weights. We test the algorithm on a set of real and synthetic test problems, and show that it produces near-optimal solutions. We compare the hybrid algorithm with other algorithms for this problem illustrating its efficiency and robustness. (c) 2005 Wiley Periodicals, Inc.
机译:域内流量工程旨在更有效地利用自治系统中的网络资源。内部网关协议(例如OSPF(开放式最短路径优先)和IS-IS(中间系统-中间系统))通常用于选择在自治系统中路由通信的路径。这些路由协议根据网络运营商分配的链路权重来引导流量。自治系统中的每个路由器都计算最短路径,并创建用于将每个数据包定向到最终目的地的路径上的下一个路由器的目的地表。给定起点-目的地对之间的一组流量需求,OSPF权重设置问题包括确定要分配给链路的权重,以便优化通常与网络拥塞措施相关的成本函数。在本文中,我们针对OSPF权重设置问题提出了一种具有局部改进过程的遗传算法。局部改进程序利用有效的动态最短路径算法在修改链路权重后重新计算最短路径。我们在一组真实和综合测试问题上对该算法进行了测试,并表明该算法产生了接近最优的解决方案。我们将混合算法与其他算法进行比较,以说明该问题的效率和鲁棒性。 (c)2005年Wiley Periodicals,Inc.

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号