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Previous work has explored measuring RRC states in a controlled setting.However, to understand the impact of these states on user-perceived performancein a wide range of contexts --- such as with a variety of device types,carriers, geographic locations, or network conditions --- a more generalapproach is needed. We have developed a tool for automatically inferring RRCstate configurations on end-user devices, without requiring any specialapplication privileges or expert knowledge. This allows us to deploy our RRCinference test on devices around the world, as well as easily track changes andtrends over time. In this talk, I will discuss the challenges of extractingthis information from arbitrary devices, as well as extending this technique tomeasure very short timers that have not yet been addressed, such as thoserelated to Discontinuous Reception (DRX) in LTE.
Talk Abstract: The growth of mobile broadband poses dual challenges for policymakers seeking to promote the healthand quality of BB services (increasingly viewed as essential infrastructure) and the efficient use of scarceradio frequency spectrum (demand for which is intensified by the growth of mobile BB). For informedpolicymaking with respect to both mandates, the FCC and other market participants need expandedaccess to real-time measurement data relating to the performance of mobile applications which typicallyare provided over wireless access. To address this challenge, we will need to create a multitieredmeasurement infrastructure, a significant component of which will involve highly distributed, end-user/edge-based measurement infrastructure (e.g., crowd-sourced, likely resident on handset or othermobile devices). This will be complemented by fixed and centralized control measurement infrastructure(e.g., SamKnows-like initiatives). The structure and relationship of these complementary measurementinfrastructures will offer opportunities for supporting new regulatory models (e.g., enforcement ofMobile BB SLAs, enforcement of spectrum sharing regimes) and will induce strategic behavior (e.g.,tussles over metric definitions, public reporting/data access, and reliance of measurements instandardization and regulatory decision-making). At an R&D level, it will require integratingperspectives from the heretofore divergent engineering communities engaged in Internet measurementand (wireless) spectrum sensing.
2) To understand and address the problems in mobile systems as they evolve over time, we need anapproach that supports long-term studies of mobile Internet traffic and the ability to interpose on theseflows. Ideally, such a system would be easy to deploy and use for a typical smartphone user running anyoperating system anywhere in the world. I present Meddle: a platform for measuring and interposing on allmobile-device Internet traffic (e.g., from smartphones and tablets). Meddle combines softwaremiddleboxes with VPN proxying, enabling both visibility and control over network flows. These featurescombine powerfully to enable new measurement tools. As examples, we have made available avisualization tool, ReCon, for users to track and control how they are being monitored by ad and analyticsservices. We also develop tools for detecting content manipulation by ISPs (Web Tripnets) and servicedifferentiation (Mobile Replay, joint work with Phillipa Gill) in the mobile environment, building uponprevious work in these areas.
Talk Abstract:Most users of home networks have experienced the intense frustration thatcomes with diagnosing poor performance. Even determining something as simpleas whether a performance problem lies with the ISP or somewhere in the homenetwork is incredibly difficult; this lack of visibility results inunnecessary service calls to ISPs and a general inability to have thenetwork perform as well as it should. In this paper, we design and developWTF (Where~Rs The Fault?), a system that reliably determines whether aperformance problem lies with the user~Rs ISP or inside the home network.The tool can also distinguish these problematic situations from the benigncase when the network is simply under-utilized. WTF uses cross-layertechniques to discover signatures of various pathologies. We implemented WTFin an off-the-shelf home router; evaluated the techniques in controlled labexperiments under a variety of operating conditions; validated it in realhomes where we can directly observe the home conditions and network setup;and deployed it in 64 home networks across 15 countries. The real-worlddeployment sheds light on common pathologies that occur in home networks. Wefind, for instance, that many users purchase fast access links butexperience significant (and frequent) performance bottlenecks in their homewireless network. In collaboration with SamKnows and the FCC, we aredeveloping a version of WTF that can be deployed on the SamKnows"whiteboxes" as part of a new in-home study program sponsored by the FCC.In addition to the WTF algorithm and our preliminary results from adeployment of WTF on the BISmark testbed, I will describe the current stateof the WTF deployment on the SamKnows hardware and our experiences as partof the FCC's pioneering efforts to support more research on this uniquetested. This project is joint work with Srikanth Sundaresan, RenataTeixeira, and others. e24fc04721
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