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Traffic classification will be a key aspect in the operation of future 5G cellular networks, where services of very different nature will coexist. Unfortunately, data encryption makes this task very difficult. To overcome this issue, flow-based schemes have been proposed based on payload-independent features extracted from the Internet Protocol (IP) traffic flow. However, such an approach relies on the use of expensive traffic probes in the core network. Alternatively, in this paper, an offline method for encrypted traffic classification in the radio interface is presented. The method divides connections per service class by analyzing only features in radio connection traces collected by base stations. For this purpose, it relies on unsupervised learning, namely agglomerative hierarchical clustering. Thus, it can be applied in the absence of labeled data (seldom available in operational cellular networks). Likewise, it can also identify new services launched in the network. Method assessment is performed over a real trace dataset taken from a live Long Term Evolution (LTE) network. Results show that traffic shares per application class estimated by the proposed method are similar to those provided by a vendor report. INDEX TERMS Traffic classification, radio access network, trace, unsupervised learning, clustering.

The properties of a web page have a strong impact on its overall loading process, including the download of its contents and their progressive rendering at the browser. As a consequence, web page content has a strong impact on the experience of web users. In this paper, we present WebCLUST, a clustering-based classification approach for web pages, which groups pages into quality-meaningful content classes impacting the Quality of Experience (QoE) of the users. Groups are defined based on standard Multipurpose Internet Mail Extensions (MIME) content breakdown and external subdomain connections, obtained through in-browser, application level measurements. Using a large corpus of multi-device, heterogeneous web content and QoE-relevant measurements for the top-500 most popular websites in the Internet, we show how WebCLUST can automatically identify relevant web content classes showing significantly different performance in terms of Web QoE relevant metrics, such as Speed Index. We additionally evaluate the impact of content caching and device type on the identification performance of WebCLUST, showing how content classes might look significantly different, depending on the access device type (desktop vs mobile), as well as when considering browser caching. Our findings suggest that Web QoE assessment should explicitly consider page content and subdomain embedding within the analysis, especially when it comes to recent work on Web QoE inference through machine learning models. To the best of our knowledge, this is the first study showing the impact of web content on Web QoE metrics, opening the door to new Web QoE assessment strategies.

Live video streaming services are gaining momentum as network and terminal capabilities improve. However, 360º live video streaming services pose new challenges due to its high bandwidth and computational requirements both on the user and service provider. In this paper, a study of the impact of the uplink of a cellular network on the performance of 360º live video streaming in YouTube is presented. Unlike previous works, the analysis focuses on the upstream between the video source and the server, not on the downstream between the server and viewers. To this end, a measurement campaign is conducted where a live video feed is transmitted and received through YouTube 360º platform in a pilot Long Term Evolution (LTE) system. During the tests, a large dataset of real traces is collected at different protocol layers, both in upstream and downstream, to check the correlation between TCP/IP metrics and key service performance indicators (e.g., video segment quality and end-to-end latency). Results show that uplink performance has a strong impact on the latency perceived by the user, which is critical for the considered live services.INDEX TERMS YouTube, live video streaming, 360-degree video, latency, Quality of Experience, uplink.

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