After a rapid deployment worldwide over the past few years, 5G is expected to have reached a mature deployment stage to provide measurable improvement of network performance and user experience over its predecessors. In this study, we aim to assess 5G deployment maturity via three conditions: (1) Does 5G performance remain stable over a long time span (1 year)? (2) Does 5G provide better performance than its predecessor Long-Term Evolution (LTE)? (3) Does the technology offer similar performance across diverse geographic areas and cellular operators? We answer this important question by conducting two year-long measurement campaigns of 5G uplink performance leveraging a custom Android app: one crowd-sourced, cross-sectional campaign spanning 8 major cities in 7 countries and two different continents (Europe and North America), and one controlled campaign focusing on mmWave deployment at a fixed location in the downtown area of Boston, MA. Our datasets show that 5G deployment in major cities appears to have matured, with no major performance improvements observed over a one-year period, but 5G does not provide consistent, superior measurable performance over LTE, especially in terms of latency, and further there exists clear uneven 5G performance across the 8 cities. Our study suggests that, while 5G deployment appears to have stagnated, it is short of delivering its promised performance and user experience gain over its predecessor.

For its stringent QoE requirement, augmented reality (AR) has been widely hailed as a representative of ultra-high bandwidth and ultra-low latency apps that will be enabled by 5G networks/edge clouds. Such a portrait of AR by the telco and cloud industry raises an important research question - can 5G enable latency-critical applications such as (edge-assisted) AR? In this paper, we conduct to our knowledge the first in-depth measurement study of whether 5G mmWave in combination with in-network edge cloud can support the baseline edge-assisted object detection. After we discover 5G mmWave is unlikely to achieve the level of uplink network performance needed to support a baseline edge-assisted object detection implementation in the near future, we quantify the performance benefits in retrofitting app-level optimizations developed in the pre-5G era on top of baseline edge-assisted object detection, as well as the performance benefits from hardware upgrade on the edge. We find that these optimizations can significantly boost object detection performance over both LTE and 5G mmWave; however, the improvement with 5G mmWave over LTE is marginal, and 5G mmWave still fails to provide satisfactory performance in all scenarios under consideration. Overall, we conclude that today's 5G mmWave deployment is not a deciding factor in enabling edge-assisted object detection.

Future WLAN devices will combine both IEEE 802.11ad and 802.11ac interfaces. The former provides multi-Gbps rates but is susceptible to blockage, whereas the latter is slower but offers reliable connectivity. A fundamental challenge is thus how to combine those complementary technologies, to make the most of the advantages they offer. In this work, we leverage Multipath TCP (MPTCP) to use both interfaces simultaneously in order to achieve a higher overall throughput as well as seamlessly switch to a single interface when the other one fails. We find that standard MPTCP often performs sub-optimally and can yield a throughput much lower than that of single path TCP over the faster of the two interfaces. We analyze the cause of these performance issues in detail and then designMuSher, an agile MPTCP scheduler that allows MPTCP to fully utilize the channel resources available to both interfaces. Our evaluation in realistic scenarios shows thatMuShercan provide a throughput improvement of 50%/130% under WLAN/Internet settings respectively, compared to the default MPTCP scheduler. It further speeds up the recovery of a traffic stream after disruption by a factor of 8x/75x.

We present an extensive experimental evaluation of the performance and power consumption of the 60 GHz IEEE 802.11ad technology on commercial smartphones. We also compare 802.11ad against its main competitors in the 5 GHz band - 802.11ac and, for first time, 802.11ax, on mobile devices. Our performance comparison focuses on two aspects that have not been extensively studied before: (i) dense multi-client and multi-AP topologies and (ii) popular mobile applications under realistic mobility patterns. Our power consumption study covers both non-communicating and communicating modes. We also present the first study of the power saving mode in 802.11ad-enabled smartphones and its impact on performance. Our results show that 802.11ad is better able to address the needs of emerging bandwidth-intensive applications in smartphones than its 5 GHz counterparts. At the same time, we identify several key research directions towards realizing its full potential.

Wireless networks operating in the 60 GHz band have the potential to provide very high throughput but face a number of challenges (e.g., high attenuation, beam training, and coping with mobility) which are widely accepted but often not well understood in practice. Understanding these challenges, and especially their actual impact on consumer-grade hardware is fundamental to fully exploit the high physical layer rates in the 60 GHz band. To this end, we perform an extensive measurement campaign using two commercial off-the-shelf 60 GHz routers in real-world environments. Our results allow us to revisit a range of issues and provide much deeper insights into the reasons for specific performance compared to prior work on performance characterization. Further, our study goes beyond basic link characterization and explores for the first time practical considerations such as coverage and access point deployment. While some of our observations are expected, we also obtain highly surprising insights that challenge the prevailing wisdom in the community. We derive the shortcomings of current commercial 60 GHz devices, and the fundamental problems that remain open on the way to fast and efficient 60 GHz networking.

We conduct one of the first extensive experimental studies of the two main link adaptation mechanisms in 60 GHz WLANs, namely rate adaptation and beam adaptation. We first show, using a variety of commodity 60 GHz devices, that simple heuristics, used by these devices to determine which the two mechanisms should be triggered, can lead to wrong decisions even in seemingly simple scenarios. We then explore for first time the feasibility of leveraging PHY layer information and ML to guide link adaptation, using a large dataset collected with a 60 GHz software-define radio testbed in a variety of indoor environments and scenarios. Finally, we design LiBRA, a practical, standard-compliant link adaptation framework that leverages ML and PHY layer information to determine when to trigger link adaptation and which adaptation mechanism to use. LiBRA strikes a balance between throughput and link recovery delay, performing close to an oracle solution, and outperforming significantly two simple heuristics used by off-the-shelf devices.

While live 360° video streaming provides an enriched viewing experience, it is challenging to guarantee the user experience against the negative effects introduced by start-up delay, event-to-eye delay, and low frame rate. It is therefore imperative to understand how different computing tasks of a live 360° streaming system contribute to these three delay metrics. Although prior works have studied commercial live 360° video streaming systems, none of them has dug into the end-to-end pipeline and explored how the task-level time consumption affects the user experience. In this paper, we conduct the first in-depth measurement study of task-level time consumption for five system components in live 360° video streaming. We first identify the subtle relationship between the time consumption breakdown across the system pipeline and the three delay metrics. We then build a prototype Zeus to measure this relationship. Our findings indicate the importance of CPU-GPU transfer at the camera and the server initialization as well as the negligible effect of 360° video stitching on the delay metrics. We finally validate that our results are representative of real world systems by comparing them with those obtained with a commercial system.

In this paper, we conduct an extensive experimental study of the two primary link adaptation mechanisms in 60 GHz WLANs, namely rate adaptation and beam adaptation, using a large data set collected from a 60 GHz software-defined radio testbed. First, we compare the effectiveness of the two mechanisms in a variety of indoor environments and scenarios, including linear and angular displacement, mobility, blockage, and interference. Next, we study the effectiveness of two rate adaptation approaches -- SNR-based rate adaptation, which has been proposed by recent works, and a learning-based approach using PHY layer information. Our results show that the former performs poorly in practical scenarios, while the latter is promising, especially when combined with online training. Finally, we explore the effectiveness of maintaining backup beams to speedup link recovery and reduce the beam training overhead. We show that this heuristic fails in scenarios involving angular displacement on the receiver side but is quite effective in most other scenarios.

With the advent of bandwidth-hungry applications and the new advancements in wireless LAN standards (802.11ad, 802.11ay) and cellular technologies (5G), modern smartphones need to be able support multi-Gbps data rates. In this work, we explore if today's smartphones are capable of handling such high-speed network traffic. Using two high-end smartphones, we show that, contrary to previous beliefs, they can indeed support Gbps data rates without significant strain on their hardware resources. Using projections, we further show that up to 12.8 Gbps could be supported with just 50% CPU utilization. Finally, we explore the factors that make this possible and the contribution of each of them.

Future WLAN devices will combine both IEEE 802.11ad and 802.11ac interfaces. The former provides multi-Gbps rates but is susceptible to blockage, whereas the latter is slower but offers reliable connectivity. A fundamental challenge is thus how to combine those complementary technologies, to make the most of the advantages they offer. In this work, we explore leveraging Multipath TCP (MPTCP) to use both interfaces simultaneously in order to achieve a higher overall throughput as well as seamlessly switching to a single interface when the other one fails. We find that standard MPTCP often performs sub-optimally and may even yield a throughput much lower than that of single path TCP over the faster of the two interfaces. We analyze the cause of these performance issues in detail and then design MuSher, an agile MPTCP scheduler that allows MPTCP to fully utilize the channel resources available to both interfaces. Our evaluation in realistic scenarios shows that MuSher provides a throughput improvement of up to 1.5x/2.3x and speeds up the recovery of a traffic stream, after disruption, by a factor of up to 8x/75x, under WLAN/Internet settings respectively, compared to the default MPTCP scheduler.

802.11ad links provide data rates up to 6.7 Gbps but remain highly susceptible to blockage and mobility. On the other hand, legacy 802.11ac/n links yield much lower rates but are robust even under dynamic scenarios. In this work, we explore using Multipath TCP (MPTCP) to engage both 802.11ad and 802.11ac interfaces simultaneously for performance speed-up and improved reliability. We show that vanilla MPTCP achieves these goals under static conditions but often results in performance worse than using the faster interface alone under dynamic scenarios. We then design and implement AMuSe, a new MPTCP scheduler that allows MPTCP to perform near-optimally under all scenarios.

Wireless networks operating in the 60 GHz band have the potential to provide very high throughput but face a number of challenges (e.g., high attenuation, beam training, and coping with mobility) which are widely accepted but often not well understood in practice. Understanding these challenges, and especially their actual impact on consumer-grade hardware is fundamental to fully exploit the high physical layer rates in the 60 GHz band. To this end, we perform an extensive measurement campaign using two commercial off-the-shelf 60 GHz routers in practical real-world environments. Our study is centered around two fundamental adaptation mechanisms in 60 GHz networks-beam training and rate control- whose interactions are key for performance. Understanding these interactions allows us to revisit a range of issues and provide much deeper insights into the reasons for specific performance compared to prior work on performance characterization. Further, our study goes beyond basic link characterization and explores for the first time practical considerations such as coverage and access point deployment. While some of our observations are expected, we also obtain highly surprising insights that challenge the prevailing wisdom in the community.