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Crowdsourcing-based mobile network tomography for xG wireless systems

机译:适用于xG无线系统的基于众包的移动网络层析成像

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Network size and number of mobile users are ever-increasing with the advancements in cellular network technologies. Hence, this situation makes the network monitoring highly complex. Although there are numerous network tomography approaches, service providers need real-time network monitoring tools to provide better network utilization. In this paper, we propose a crowdsourcing-based real-time network tomography framework. In the proposed framework, channel condition and user data usage are monitored via an application at the mobile terminals, and then the mobile terminals transmit their data to the server. In this way, the network and user behavior can be continuously monitored, and real-time actions can be implemented to improve the network performance. By using the proposed framework, we propose an optimization framework for the amount and reporting frequency of the transmitted data to avoid battery drain at the mobile terminal and network congestion. At the end, we provide simulation results for the proposed optimization framework.
机译:随着蜂窝网络技术的发展,网络规模和移动用户数量不断增加。因此,这种情况使网络监视变得非常复杂。尽管有许多网络层析成像方法,但是服务提供商需要实时网络监视工具来提供更好的网络利用率。在本文中,我们提出了一种基于众包的实时网络层析成像框架。在提出的框架中,通过移动终端处的应用来监视信道状况和用户数据使用,然后移动终端将其数据发送到服务器。这样,可以连续监视网络和用户行为,并可以实施实时操作以提高网络性能。通过使用提出的框架,我们为传输的数据的数量和报告频率提出了一个优化框架,以避免移动终端的电池消耗和网络拥塞。最后,我们为提出的优化框架提供了仿真结果。

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