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NextG cellular networks are designed to meet Quality of Service requirements for various applications in and beyond smartphones and mobile devices. However, lacking introspection into the 5G Radio Access Network (RAN) application and transport layer designers are ill-poised to cope with the vagaries of the wireless last hop to a mobile client, while 5G network operators run mostly closed networks, limiting their potential for co-design with the wider internet and user applications. This paper presents NR-Scope, a passive, incrementally-deployable, and independently-deployable Standalone 5G network telemetry system that can stream fine-grained RAN capacity, latency, and retransmission information to application servers to enable better millisecond scale, application-level decisions on offered load and bit rate adaptation than end-to-end latency measurements or end-to-end packet losses currently permit. Our experimental evaluation on various 5G Standalone base stations demonstrates NR-Scope can achieve less than 0.1% throughput error estimation for every UE in a RAN. The code is available at https://github.com/PrincetonUniversity/NR-Scope. 

5G New Radio cellular networks are designed to provide high Quality of Service for application on wirelessly connected devices. However, changing conditions of the wireless last hop can degrade application performance, and the applications have no visibility into the 5G Radio Access Network (RAN). Most 5G network operators run closed networks, limiting the potential for co-design with the wider-area internet and user applications. This paper demonstrates NR-Scope, a passive, incrementally-deployable, and independently-deployable Standalone 5G network telemetry system that can passively measure fine-grained RAN capacity, latency, and retransmission information. Application servers can take advantage of the measurements to achieve better millisecond scale, application-level decisions on offered load and bit rate adaptation than end-to-end latency measurements or end-to-end packet losses currently permit. We demonstrate the performance of NR-Scope by decoding the downlink control information (DCI) for downlink and uplink traffic of a 5G Standalone base station in real-time. 

The Internet Route Registry (IRR) and Resource Public Key Infrastructure (RPKI) both emerged as different solutions to improve routing security in the Border Gateway Protocol (BGP) by allowing networks to register information and develop route filters based on information other networks have registered. RPKI is a crypto system, with associated complexity and policy challenges; it has seen substantial but slowing adoption. IRR databases often contain inaccurate records due to lack of validation standards. Given the widespread use of IRR for routing security purposes, this inaccuracy merits further study. We study IRR accuracy by quantifying the consistency between IRR and RPKI records, analyze the causes of inconsistency, and examine which ASes are contributing correct IRR information. In October 2021, we found ROAs for around 20% of RADB IRR records, and a consistency of 38% and 60% in v4 and v6. For RIPE IRR, we found ROAs for 47% records and a consistency of 73% and 82% in v4 and v6. For APNIC IRR, we found ROAs for 76% records and a high consistency of 98% and 99% in v4 and v6. For AFRINIC IRR, we found ROAs for only 4% records and a consistency of 93% and 97% in v4 and v6. 

Using a toolbox of Internet cartography methods, and new ways of applying them, we have undertaken a comprehensive active measurement-driven study of the topology of U.S. regional access ISPs. We used state-of-the-art approaches in various combinations to accommodate the geographic scope, scale, and architectural richness of U.S. regional access ISPs. In addition to vantage points from research platforms, we used public WiFi hotspots and public transit of mobile devices to acquire the visibility needed to thoroughly map access networks across regions. We observed many different approaches to aggregation and redundancy, across links, nodes, buildings, and at different levels of the hierarchy. One result is substantial disparity in latency from some Edge COs to their backbone COs, with implications for end users of cloud services. Our methods and results can inform future analysis of critical infrastructure, including resilience to disasters, persistence of the digital divide, and challenges for the future of 5G and edge computing.