通过在线模拟优化OSPF的权重,使丢包最小化

H. T. Kaur, Tao Ye, S. Kalyanaraman, K. Vastola
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引用次数: 23

摘要

在本文中,我们提出了一种通过在线仿真优化链路权重来最小化OSPF网络中丢包的方案。我们选择网络中的丢包率作为优化指标,因为它是一个很好的拥塞指标,并影响底层应用程序的性能。我们根据链路参数,如带宽和缓冲空间,以及流量需求参数,制定了网络中的丢包率。采用GI/M/1/K排队模型计算给定链路上的丢包概率。即使对于线性目标函数Bernard Fortz和Mikkel Thorup(2000),优化OSPF权重的问题也被认为是np困难的。我们使用在线模拟(OLS)框架T. Ye等人(2001)来寻找一个好的链路权重设置,并作为自动网络管理的工具。OLS使用快速、可扩展的递归随机搜索(RRS)算法来搜索参数空间。我们的结果表明,与局部搜索启发式Bernard Fortz和Mikkel Thorup(2000)相比,RRS需要的函数评估减少了50-90%,以找到一个“好的”链接权重设置。改进的数量取决于网络拓扑、流量条件和优化度量。我们使用ns对提出的OSPF优化方案进行了仿真,结果表明,对于所考虑的流量和拓扑结构,总丢包率提高了30-60%。
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Minimizing packet loss by optimizing OSPF weights using online simulation
In this paper, we present a scheme for minimizing packet loss in OSPF networks by optimizing link weights using online simulation. We have chosen packet loss rate in the network as the optimization metric as it is a good indicator of congestion and impacts the performance of the underlying applications. We have formulated packet loss rate in the network in terms of the link parameters, such as bandwidth and buffer space, and the parameters of the traffic demands. A GI/M/1/K queuing model has been used to compute the packet drop probability on a given link. The problem of optimizing OSPF weights is known to be NP-hard even for the case of a linear objective function Bernard Fortz and Mikkel Thorup (2000), We use online simulation (OLS) framework T. Ye et al. (2001) to search for a good link weight setting and as a tool for automatic network management. OLS uses fast, scalable recursive random search (RRS) algorithm to search the parameter space. Our results demonstrate that the RRS takes 50-90% fewer function evaluations as compared to the local search heuristic Bernard Fortz and Mikkel Thorup (2000) of to find a "good" link weight setting. The amount of improvement depends on the network topology, traffic conditions and optimization metric. We have simulated the proposed OSPF optimization scheme using ns and our results demonstrate improvements of the order of 30-60% in the total packet drop rate for the traffic and topologies considered.
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