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Traps and pitfalls of using contact traces in performance studies of opportunistic networks

机译:在机会网络的性能研究中使用接触痕迹的陷阱和陷阱

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Contact-based simulations are a very popular tool for the analysis of opportunistic networks. They are used for evaluation of networking metrics, for quantifying the effects of infrastructure and for the design of forwarding strategies. However, little evidence exists that the results of such simulations accurately describe the performance of opportunistic networks, as they commonly ignore some important factors (like limited transmission bandwidth) or they rely on assumptions such as infinite user cache sizes. In order to evaluate this issue, we design a testbed with a real application and real users; we collect application data in addition to the contact traces and compare measured performance to the results of the contact-based simulations. We find that contact-based simulations significantly overestimate delivery ratio, while the captured delay tends to be 2-3 times lower than the experimentally obtained delay. We show that assuming infinite cache sizes leads to misinterpretation of the effects of backbone on an opportunistic network. Finally, we show that contact traces can be used to analytically estimate the delivery ratios and the impact of backbone, through the dependency between a user centrality measure and her delivery ratio.
机译:基于接触的仿真是机会网络分析中非常流行的工具。它们用于评估网络指标,量化基础架构的影响以及设计转发策略。但是,几乎没有证据表明这种模拟的结果准确地描述了机会网络的性能,因为它们通常会忽略一些重要因素(例如有限的传输带宽)或依赖于无限用户缓存大小等假设。为了评估此问题,我们设计了一个具有真实应用程序和真实用户的测试平台。我们不仅收集接触迹线,还收集应用程序数据,并将测得的性能与基于接触的仿真结果进行比较。我们发现,基于接触的模拟显着高估了交付率,而捕获的延迟往往比实验获得的延迟低2-3倍。我们证明了假设无限的高速缓存大小会导致对机会网络中主干网的影响的误解。最后,我们表明,通过用户集中度度量与其交付比率之间的依赖关系,联系跟踪可用于分析性地评估交付比率和骨干网的影响。

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