Diego Madariaga, Lucas Torrealba, Javier Madariaga, Javier Bustos-Jiménez, B. Bustos
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引用次数: 1
摘要
在所有的互联网服务质量(QoS)指标中,往返时间(RTT)、抖动(jitter)和丢包(packet loss)对整个网络的性能和用户感知的体验质量(Quality of Experience, QoE)有很大的影响,因此得到了深入的研究。考虑到这一点,我们通过被动地监控用户空间中的网络,设法生成了一个真实世界的数据集,其中包含了这些重要质量指标的全面背景化。为了生成这个数据集,我们首先为Android设备开发了一种新颖的周期性被动Ping (PePa Ping)方法。与其他工作不同,PePa Ping定期获取所有TCP连接的RTT、抖动和丢包数。这种被动方式依赖于在客户端设备内实现一个本地VPN服务器来管理所有Internet流量并获取所建立连接的QoS信息。收集到的QoS指标由Linux内核直接提供,因此,它们非常接近用户设备体验到的真实QoS值。此外,PePa Ping应用程序不断测量与每个单独的网络流量、设备状态和互联网连接状态(WiFi或移动)相关的其他指标。有了所有收集到的信息,每个网络流都可以精确地与一组环境数据联系起来,这些数据可以提供每个单独连接的综合背景。
PePa Ping Dataset: Comprehensive Contextualization of Periodic Passive Ping in Wireless Networks
Among all Internet Quality of Service (QoS) indicators, Round-trip time (RTT), jitter and packet loss have been thoroughly studied due to their great impact on the overall network's performance and the Quality of Experience (QoE) perceived by the users. Considering that, we managed to generate a real-world dataset with a comprehensive contextualization of these important quality indicators by passively monitoring the network in user-space. To generate this dataset, we first developed a novel Periodic Passive Ping (PePa Ping) methodology for Android devices. Contrary to other works, PePa Ping periodically obtains RTT, jitter, and number of lost packets of all TCP connections. This passive approach relies on the implementation of a local VPN server residing inside the client device to manage all Internet traffic and obtain QoS information of the connections established. The collected QoS indicators are provided directly by the Linux kernel, and therefore, they are exceptionally close to real QoS values experienced by users' devices. Additionally, the PePa Ping application continuously measured other indicators related to each individual network flow, the state of the device, and the state of the Internet connection (either WiFi or Mobile). With all the collected information, each network flow can be precisely linked to a set of environmental data that provides a comprehensive contextualization of each individual connection.