使用Cloudlab测试智能DTN路由

R. Lent, Gandhimathi Velusamy
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引用次数: 0

摘要

使用CloudLab和专用实验室测试平台进行了一系列实验,以测试认知空间网关(CSG)的性能。CSG是DTN路由的一种方法,利用峰值神经网络作为学习元素来发现和动态转发数据包。实验的重点是评估在给定流量强度下在模拟空间网络上发送的数据包的平均响应时间和数据流的吞吐量。在两个设施上运行相同的拓扑结构和相同的可重复测试。结果有助于通过独立的实验设置验证CSG路由方法与接触图路由算法的性能。此外,实验揭示了一些与使用网络虚拟化相关的挑战,如在CloudLab中所做的,当应用于网络性能测量时。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Testing Smart DTN Routing Using Cloudlab
A series of experiments were conducted using both CloudLab and a dedicated laboratory testbed to test the performance of the Cognitive Space Gateways (CSG)-an approach to DTN routing that exploits a spiking neural network as a learning element to discover and dynamically forward data bundles. The experiments focus on evaluating the average response time of bundles and throughput of a data flow sent at given traffic intensity over an emulated space network. The same topology and identical, repeatable tests were run on both facilities. The results help to validate the performance of the CSG routing approach compared to the Contact Graph Routing algorithm using independent experimental settings. Furthermore, the experiments reveal some of the challenges associated to the use of network virtualization, as done in CloudLab, when applied to network performance measurements.
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