Real-time mobile applications such as AR/VR, cloud gaming, and collaborative robotics rely on edge computing to maintain ultra-low latency, yet they can suffer noticeable service interruptions when users move because the application's session state must migrate to a new edge site. We present EdgeWarp, a system that delivers instant mobility for stateful edge applications over 5G while laying the groundwork for 6G. EdgeWarp employs a two-step synchronization protocol that proactively mirrors application state at edge sites predicted to serve the user next, sharply reducing transfer delays, and it signals each session's latency budget to the 5G control plane so that critical flows are prioritized during handover. Experiments with real applications and 4G/5G radio traces show that EdgeWarp cuts mobility-induced downtime by up to 15.4×, charting a path toward zero-downtime edge computing—a prerequisite for emerging 6G scenarios such as holographic telepresence, tactile Internet, and large-scale digital twins. We have made our anonymized code publicly accessible here.

Popular video streaming platforms attract a large number of global marketers who use the platform to advertise their services. While benefiting platforms and advertisers, users are burdened with the costs of advertisements. Users not only pay for these ads with their invested time and personal information, but also through a substantial amount of data translating into direct financial cost. The financial cost becomes even more pronounced in developing countries, where the cost of mobile broadband can be disproportionately high relative to average income levels. In this paper, we perform the first independent and empirical analysis of the data costs of mobile video ads on YouTube, the most popular video platform, from the users' perspective. To do so, we collect and analyze a data set of over 46,000 YouTube video ads. We find that streaming video ads have multiplelatent andavoidable sources of data wastage, which can lead to excessive data consumption by users. We also conduct an affordability analysis to quantify the overall impact of data wastage and reveal the specific data costs per country associated with these losses. Our findings highlight the need for video platform providers, such as YouTube, to minimize data wastage linked to ads, to make their services more affordable and inclusive.

As a popular choice for video and entertainment streaming, YouTube hosts a large audience, including children, who form a growing proportion of its users. Despite separate "made for kids" labelling and stricter moderation of these videos, inappropriate advertising remains a concern as it threatens the safety of YouTube for young viewers. This paper is the first comparative measurement study that explores how advertisement exposure and content vary across child-oriented videos on YouTube. We do this by conducting a cross-regional advertisement analysis on highly viewed "made for kids" labelled content across a total of ten countries with varying regulation. A second front of comparison is carried out between ad patterns on unlabelled and labelled child-oriented videos. Our analysis reveals that the safety of a child's YouTube experience is shaped significantly by their external environment. There also appears to be lax enforcement of YouTube ad and child protection policies, indicated by the presence of unlabelled child-oriented content with weak ad regulation. We discuss the implications of inappropriate exposure on children and suggest policy and implementation measures to mitigate this threat.

Today's Web remains too expensive for many Internet users, especially in developing regions. Unfortunately, the rising complexity of the Web makes affordability an even bigger concern as it stands to limit users' access to Internet services. We propose a novel framework and a fairness metric for rethinking Web architecture for affordability and inclusion. Our proposed framework systematically adapts Web complexity based on geographic variations in mobile broadband prices and income levels. We conduct a cross-country analysis of 99 countries, showing that our framework can better balance affordability and webpage quality while preserving user privacy. To adapt Web complexity, our framework solves an optimization problem to produce webpages that maximize page quality while reducing the webpage to a given target size.

Public service websites act as official gateways to services provided by governments. Many of these websites are essential for citizens to receive reliable information and online government services. However, the lack of affordability of mobile broadband services in many developing countries and the rising complexity of websites create barriers for citizens in accessing these government websites. This paper presents the first large-scale analysis of the affordability of public service websites in developing countries. We do this by collecting a corpus of 1900 public service websites, including public websites from nine developing countries and for comparison websites from nine developed countries. Our investigation is driven by website complexity analysis as well as evaluation through a recently proposed affordability index. Our analysis reveals that, in general, public service websites in developing countries do not meet the affordability target set by the UN’s Broadband Commission. However, we show that several countries can be brought within or closer to the affordability target by implementing webpage optimizations to reduce page sizes. We also discuss policy interventions that can help make access to public service website more affordable.

5G and next-generation cellular networks aim to support tactile internet to enable immersive and real-time applications by providing ultra-low latency and extremely high reliability. This imposes new requirements on the design of cellular core networks. A key component of the cellular core is the control plane. Time to complete cellular control plane operations (e.g., mobility handoff, service establishment) directly impacts the delay experienced by end-user applications. In this paper, we design Neutrino, a cellular control plane that provides users an abstraction of reliable access to cellular services while ensuring lower latency. Our testbed evaluations based on real cellular control traffic traces show that Neutrino provides an improvement in control procedure completion times by up to$3.1\times $without failures, and up to$5.6\times $under control plane failures, over existing 5G. We also show how these improvements translate into improving end-user application performance: for AR/VR applications and self-driving cars, Neutrino improves performance by up to$2.5\times $and$2.8\times $, respectively.

5G networks are considered potential enablers for many emerging edge applications, such as those related to autonomous vehicles, virtual and augmented reality, and online gaming. However, recent works have shown the cellular control plane is a potential bottleneck in enabling such applications --- control plane operations are slow, frequent, and can directly impact the delay experienced by end-user applications. Moreover, failures in the cellular control plane can significantly degrade application performance. In this paper, we consider the problem of enabling latency-sensitive and safety-critical edge applications on 5G networks. We identify fundamental control plane design challenges and posit enabling these applications requires re-thinking the cellular control plane. We propose a new edge-based cellular control plane, CellClone, which provides fast and fault-tolerant control plane processing. CellClone employs multiple active control plane clones at the network edge to mask control plane faults and speedup control processing. Central to its design is a custom quorum-based consistency protocol that provides state consistency with low latency. Testbed evaluations using real cellular traces show a median improvement of more than 3.8× in speeding up control plane operations with outright node failures and stragglers. These improvements translate into better application performance; with CellClone, autonomous cars and VR applications reduce missed application deadlines by more than 90%.

The popularity of video streaming on smartphones has led to rising demands for high-quality mobile video streaming. Consequently, we are observing growing support for higher resolution videos (e.g., HD, FHD, QHD) and higher video frame rates (e.g., 48 FPS, 60 FPS). However, supporting high-quality video streaming on smartphones introduces new challenges---besides the available network capacity, the smartphone itself can become a bottleneck due to resource constraints, such as low available memory. In this paper, we conduct an in-depth investigation of memory usage on smartphones and its impacts on mobile video streaming. Our investigation - driven by a combination of a user study, user survey, and experiments on real smartphones - reveals that (i) most smartphones observe memory pressure (i.e., low available memory scenarios), (ii) memory pressure can have a significant impact on mobile video QoE when streaming high-quality videos, e.g., resulting in the mean frame drop rate of 9--100% across smartphones and significantly lower user ratings, and (iii) the drop in mobile video QoE happens primarily due to the way in which video processes interact with kernel-level memory management mechanism, with opportunities for improving mobile video QoE through better adaptation by video clients.

The rapid growth in the number of entry-level smartphones and mobile broadband subscriptions in developing countries has served as a motivation for several projects focused on improving mobile users' quality of experience (QoE). One such initiative is the development of Android Go, a customized operating system designed to run over entry-level smartphones. Today, more than 80% entry-level Android smartphones run Android Go. Despite its growing popularity, its effectiveness in improving the Web QoE remains unclear. This paper presents the first independent empirical analysis of Android Go's causal impact on mobile Web performance. We use a combination of controlled experiments and a set of methodological approaches from the econometrics literature to find unbiased estimates of the average causal effect. Our analysis provides insights that have implications for different stakeholders in the ecosystem of entry-level devices.

Today's Web remains too expensive for many Internet users, especially in developing regions. Unfortunately, the rising complexity of the Web makes affordability an even bigger concern as it stands to limit users' access to Internet services. We propose a novel framework and fairness metric for rethinking Web architecture for affordability and inclusion. Our framework provides systematic guidelines for adapting Web complexity based on geographic variations in mobile broadband prices and income levels. Preliminary evaluation shows the resulting architecture can achieve a better balance between Web quality and affordability while preserving user privacy.

5G networks aim to provide ultra-low latency and higher reliability to support emerging and near real-time applications such as augmented and virtual reality, remote surgery, self-driving cars, and multi-player online gaming. This imposes new requirements on the design of cellular core networks. A key component of the cellular core is the control plane. Time to complete control plane operations (e.g. mobility handoff, service establishment) directly impacts the delay experienced by end-user applications. In this paper, we design Neutrino, a cellular control plane that provides users an abstraction of reliable access to cellular services while ensuring lower latency. Our testbed evaluations based on real cellular control traffic traces show that Neutrino provides an improvement in control procedure completion times by up to 3.1x without failures, and up to 5.6x under control plane failures, over existing cellular core proposals. We also show how these improvements translate into improving end-user application performance: for AR/VR applications and self-driving cars, Neutrino performs up to 2.5x and up to 2.8x better, respectively, as compared to existing EPC.

Web Light is a transcoding service introduced by Google to show lighter and faster webpages to users searching on slow mobile clients. The service detects slow clients (e.g., users on 2G) and tries to convert webpages on the fly into a version optimized for these clients. Web Light claims to significantly reduce page load times, save user data, and substantially increase traffic to such webpages. However, there are several concerns around this service, including, its effectiveness in, preserving relevant content on a page, showing third-party advertisements, improving user performance as well as privacy concerns for users and publishers.

Cellular traffic continues to grow rapidly making the scalability of the cellular infrastructure a critical issue. However, there is mounting evidence that the current Evolved Packet Core (EPC) is ill-suited to meet these scaling demands: EPC solutions based on specialized appliances are expensive to scale and recent software EPCs perform poorly, particularly with increasing numbers of devices or signaling traffic.

Conventional static datacenter (DC) network designs offer extreme cost vs. performance tradeoffs---simple leaf-spine networks are cost-effective but oversubscribed, while "fat tree"-like solutions offer good worst-case performance but are expensive. Recent results make a promising case for augmenting an oversubscribed network with reconfigurable inter-rack wireless or optical links. Inspired by the promise of reconfigurability, this paper presents FireFly, an inter-rack network solution that pushes DC network design to the extreme on three key fronts: (1) all links are reconfigurable; (2) all links are wireless; and (3) non top-of-rack switches are eliminated altogether. This vision, if realized, can offer significant benefits in terms of increased flexibility, reduced equipment cost, and minimal cabling complexity. In order to achieve this vision, we need to look beyond traditional RF wireless solutions due to their interference footprint which limits range and data rates. Thus, we make the case for using free-space optics (FSO). We demonstrate the viability of this architecture by (a) building a proof-of-concept prototype of a steerable small form factor FSO device using commodity components and (b) developing practical heuristics to address algorithmic and system-level challenges in network design and management.

We present a framework, Atlas, which incorporates application-awareness into Software-Defined Networking (SDN), which is currently capable of L2/3/4-based policy enforcement but agnostic to higher layers. Atlas enables fine-grained, accurate and scalable application classification in SDN. It employs a machine learning (ML) based traffic classification technique, a crowd-sourcing approach to obtain ground truth data and leverages SDN's data reporting mechanism and centralized control. We prototype Atlas on HP Labs wireless networks and observe 94% accuracy on average, for top 40 Android applications.

Networks today rely on middleboxes to provide critical performance, security, and policy compliance capabilities. Achieving these benefits and ensuring that the traffic is directed through the desired sequence of middleboxes requires significant manual effort and operator expertise. In this respect, Software-Defined Networking (SDN) offers a promising alternative. Middleboxes, however, introduce new aspects (e.g., policy composition, resource management, packet modifications) that fall outside the purvey of traditional L2/L3 functions that SDN supports (e.g., access control or routing).