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引用次数: 1

摘要

动态自适应路由是提高分组无线网络生存能力的必要条件。为了满足需求,选择了开放最短路径优先(OSPF)版本2。网络连接状态在高度机动的战术环境中经常迅速变化(由于干扰和站点中断/增加),必须通过协议动态和自动更新以保持可靠的网络服务。通过快速更新,拓扑数据库将更加最新,路由决策将更加优化。然而,高的更新率会消耗更多的信道带宽,并对用户流量产生不利影响。目标是优化OSPF协议,使系统在预期的流量负载和网络场景下保持可接受的性能。与更新过程相关的定时参数将会变化,以确定最佳设置。这些更新以OSPF报文的形式传递,称为lsu (link state updates)。LSU数据包将在信道利用率上与用户流量竞争。为了减少对用户流量的影响,需要对OSPF协议参数进行优化,减少开销流量。为此开发了一个详细的仿真模型。我们描述了使用鲁棒设计方法结合仿真模型来优化动态路由协议。稳健设计方法的主要优点是为确定最具影响力的控制因素所需的实验提供了一种有纪律的方法(即,不需要运行所有可能的实验组合)。
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Optimization of routing protocol for packet radio networks
Dynamic adaptive routing is required to improve the survivability of a packet radio network. A protocol called Open Shortest Path First (OSPF) Version 2 has been selected to meet the requirement. The network connectivity status, which often changes rapidly in a highly mobile tactical environment (due to jamming and station outages/additions), must be updated dynamically and automatically by the protocol to maintain reliable network service. With fast updates, the topology database will be more up-to-date and routing decisions will be more optimum. However high update rate will consume more channel bandwidth and will have adverse impact on user traffic. The objective is to optimize the OSPF protocol such that the system will maintain acceptable performance under anticipated traffic loading and network scenarios. The timing parameters associated with the update process will be varied to determine the optimum settings. The updates are transmitted in OSPF packets called link state updates (LSUs). The LSU packets will compete with user traffic on channel utilization. To reduce the impact on user traffic, the OSPF protocol parameters will be optimized to reduce the overhead traffic. A detailed simulation model has been developed for this effort. We describe the use of the robust design method in conjunction with the simulation model to optimize the protocol for dynamic routing. The main advantage of the robust design method is to provide a disciplined approach for experimentation (i.e., with no need to run all possible combinations of the experiment) that is needed to determine the most influential control factors.
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