Mobile broadband is the dominant mode of Internet access across the Global South, yet independent quality assessment remains fundamentally limited. Crowdsourced platforms capture only where motivated users run speed tests, while standard administrative aggregation collapses communities with vastly different connectivity realities into a single metric — together rendering marginalized communities invisible to measurement. We construct iQoE, a normalized broadband quality index derived from crowdsourced data, and show that measurement density correlates strongly with wealth while national progress narratives obscure deep spatial inequality. To reach communities iQoE cannot see, we propose a mixed-methods approach: a lightweight Android app paired with a diary study in Korail — Bangladesh's largest urban slum — triangulated against network planner interviews. We seek SIGCOMM community feedback on measurement design for underserved urban contexts in the Global South.

Existing LEO satellite network simulators widely approximate satellite coverage using a cone-based model that assumes uniform capacity distribution within a satellite's field of view. However, modern systems employ phased-array antennas that impose discrete beam constraints, fundamentally altering coverage characteristics. In this paper, we investigate the extent to which ignoring beam-level constraints biases network-level performance estimates. We introduce a simplified beam-aware model that captures beam count, capacity, and limited spatial reuse, and compare it against traditional cone-based approximations across a range of user distributions. Our results show that cone models can significantly overestimate service coverage, particularly under sparse or highly clustered demand, due to beam-count and beam-capacity exhaustion effects. We further analyze how beam-hopping and -stacking mitigate these limitations and quantify their impact on predicted coverage differences, demonstrating reductions in predicted coverage difference of 40% and 65% respectively. We position these results of our model as the first step towards higher-fidelity simulation to show the importance of modeling beams and we sketch directions for future work that further improves fidelity.

Support for roaming in today's cellular architecture involves operating a private network that sits right next to the mainstream Internet. This network is called the IP Exchange Network (IPX) and it provides Mobile Network Operators (MNOs) with a mechanism to form roaming partnerships, resolve billing and QoS, and set up tunnels as necessary. We propose a design which we call the CPX (Consolidated IPX/IXP) where the roaming network converges with the Internet by leveraging existing edge providers to provide all the benefits that the IPX network provides. In addition to convergence, the CPX architecture provides lower latency for roaming users; in our simulation of a global CPX deployment, we demonstrate an average of 318% improvement in roaming connection latency.

Low Earth Orbit (LEO) satellite constellations, such as Starlink, are increasingly promoted as a solution to the digital divide in rural and underserved communities. In this paper, we take a closer look at the limits of this approach. Using the insight that capacity limitations of LEO-based access networks are driven by peak demand density, we introduce a simple analytical model that brings together real-world demand data with the physical and regulatory limits of LEO satellite networks. Applying our model to broadband demand across the United States, we find that serving the current Starlink constellation size is likely insufficient for covering all un- and underserved locations in the US and we find diminishing returns that disincentivize scaling the constellation to serve the long-tail of these un(der)served locations. We also identify that Starlink's current pricing is likely unaffordable for the majority of these locations, even with existing government subsidies. We argue that LEO constellations, while technologically impressive, are just another piece of the solution, rather than a panacea. New, innovative approaches are still required to end the digital divide.

We propose Roaming-in-Place (RinP), a technique for dynamically sharing capacity across mobile network operators. RinP is a new form of infrastructure sharing that expands the traditional notion of roaming in cellular networks such that users may roam between operators with overlapping coverage areas based on load and performance conditions. Using simulation and small-scale experiments, we show that deploying RinP would allow operators to run their networks at higher utilization and provide users with higher availability and performance, while achieving 30–40% infrastructure savings in our typical evaluation scenarios. We present a design for RinP that can be incrementally deployed with modest changes to existing cellular infrastructure. We build a prototype RinP testbed, and show that our proposed design can be realized feasibly with modest changes to existing cellular infrastructure, requires no change to current protocol standards, and adds minimal latency overheads.

The FCC's National Broadband Map aspires to provide an unprecedented view into broadband availability in the US. However, this map, which also determines eligibility for public grant funding, relies on self-reported data from service providers that in turn have incentives to strategically misrepresent their coverage. In this paper, we develop an approach for automatically identifying these low-quality service claims in the National Broadband Map. To do this, we develop a novel dataset of broadband availability consisting of 750k observations from more than 900 US ISPs, derived from a combination of regulatory data and crowdsourced speed tests. Using this dataset, we develop a model to classify the accuracy of service provider regulatory filings and achieve AUCs over 0.98 for unseen examples. Our approach provides an effective technique to enable policymakers, civil society, and the public to identify portions of the National Broadband Map that are likely to have integrity challenges.

Markets in which competition thrives are good for both consumers and innovation but, unfortunately, competition is not thriving in the increasingly important cellular market. We propose CellBricks, a novel cellular architecture that lowers the barrier to entry for new operators by enabling users to consume access on-demand from any available cellular operator — small or large, trusted or untrusted. CellBricks achieves this by moving support for mobility and user management (authentication and billing) out of the network and into end hosts. These changes, we believe, bring valuable benefits beyond enabling competition: they lead to a cellular infrastructure that is simpler and more efficient.

In the last decade, billions of people worldwide have upgraded from basic 2G feature phones to data-enabled 4G smartphones. In most cases, people upgrade in areas with 4G coverage (typically cities and large towns), but increasingly, people choose to upgrade in areas that only have 2G coverage or no cellular coverage at all. This counterintuitive behavior -- upgrading your phone despite living in an area that does not actively support many of the features of that new device -- is the focus of this work.

The smartphone has been touted as the technology of the 21st century. Global smartphone adoption rates are growing rapidly, up to over 24% in 2014, with usage increasing 25% in the last year. However, rural areas are often the last places to benefit from these technological trends. Utilizing cellular network registration logs, we explore the adoption and usage of smartphones in an extremely remote community in Indonesia. We found that 16% of the phones in the area were smartphones (compared to between 14--24% in Indonesia). This shows that smartphone adoption in rural Indonesia is similar to the rest of the country. We also explored usage in the network, and found that smartphone users were more likely to text, especially to other smartphone users.

Over five billion people are active cellular subscribers, spending over a trillion dollars a year on communications. Despite this, hundreds of millions of people are still not connected.

Networking research would be well served by the adoption of a set of traffic benchmarks to model network applications for empirical evaluations; such benchmarks are common in many other areas of computing. While it has long been known that certain aspects of modeling traffic, such as round trip time, can dramatically affect application and network performance, there is still no agreement as to how such components should be controlled within an experiment. In this paper we advance the discussion of standards for empirical networking research by demonstrating how certain components of network traffic, such as the structure of application data exchanges within a TCP connection, can have a larger impact on the results obtained through experimentation than other dimensions of traffic such as round-trip time. Such findings point to the pressing need for traffic benchmarks in networking research. Through testbed experiments performed with synthetically generated network traffic from two very different traffic sources, and using several models of TCP connection structure, we demonstrate the strong effects of connection structure in traffic workload modeling on performance measures such as queue length at routers, number of active connections in the network, user response times, and connection durations.

Modern enterprises almost ubiquitously deploy middlebox processing services to improve security and performance in their networks. Despite this, we find that today's middlebox infrastructure is expensive, complex to manage, and creates new failure modes for the networks that use them. Given the promise of cloud computing to decrease costs, ease management, and provide elasticity and fault-tolerance, we argue that middlebox processing can benefit from outsourcing the cloud. Arriving at a feasible implementation, however, is challenging due to the need to achieve functional equivalence with traditional middlebox deployments without sacrificing performance or increasing network complexity.