Video analytics with deep learning techniques has generated immense interest in academia and industry, captivating minds with its transformative potential. Deep learning techniques and the deluge of video data enable the mechanization of tasks that were once the exclusive domain of human effort. Furthermore, edge intelligence is emerging as an interdisciplinary technology that drives the fusion of edge computing and artificial intelligence (AI). Edge computing allows the Internet of Things (IoT) devices with limited resources to offload their compute-intensive AI applications to the network edge servers for execution. Specifically, AI workloads for video analytics can be moved to the network edge from the cloud, providing improved latency and bandwidth savings, among other benefits. This article reviews current technologies used in Edge AI-assisted video analytics in smart cities. It examines the various artificial intelligence models and privacy-preserving techniques used in edge video analytics. It identifies the various applications of video analytics in smart cities, including security and surveillance, transportation and traffic management, healthcare, education, sports and entertainment, and many more. Besides, it highlights the challenges of edge video analysis and open research issues. It is expected that this review will be valuable for researchers, engineers, and decision-makers who want to understand the landscape and scale of edge video analytics in smart cities. 

Opportunities, Applications, and Challenges of Edge-AI Enabled Video Analytics in Smart Cities: A Systematic Review

As discussions around 6G begin, it is important to carefully quantify the spectral efficiency gains actually realized by deployed 5G networks as compared to 4G through various enhancements such as higher modulation, beamforming, and MIMO. This will inform the design of future cellular systems, especially in the mid-bands, which provide a good balance between bandwidth and propagation. Similar to 4G, 5G also utilizes low-band (<1 GHz) and mid-band spectrum (1 to 6 GHz), and hence comparing the performance of 4G and 5G in these bands will provide insights into how further improvements can be attained. In this work, we address a crucial question: is the performance boost in 5G compared to 4G primarily a result of increased bandwidth, or do the other enhancements play significant roles, and if so, under what circumstances? Hence, we conduct city-wide measurements of 4G and 5G cellular networks deployed in low- and mid-bands in Chicago and Minneapolis, and carefully quantify the contributions of different aspects of 5G advancements to its improved throughput performance. Our analyses show that (i) compared to 4G, the throughput improvement in 5G today is mainly influenced by the wider channel bandwidth, both from single channels and channel aggregation, (ii) in addition to wider channels, improved 5G throughput requires better signal conditions, which can be delivered by denser deployment and/or use of beamforming in mid-bands, (iii) the channel rank in real-world environments rarely supports the full 4 layers of 4x4 MIMO and (iv) advanced features such as MU-MIMO and higher order modulation such as 1024-QAM have yet to be widely deployed. These observations and conclusions lead one to consider designing the next generation of cellular systems to have wider channels, perhaps with improved channel aggregation, dense deployment with more beams.

pdf/a-comprehensive-real-world-evaluation-of-5g-improvements-52vxv1el60.pdf

A Comprehensive Real-World Evaluation of 5G Improvements over 4G in Low- and Mid-Bands

In this paper, we study an important, yet unexplored problem of configuration dependencies in 5G/4.5G radio resource control (RRC). Different from the previous studies in 3G/4G networks, 5G/4.5G allows more than one cells to serve a mobile device, resulting in more configuration dynamics and complexity that vary with all the serving cells. We analyze inter-dependency among configurations, categorize dependent misconfigurations, uncover their root causes, and quantify negative performance impacts. Specifically, we formulate configuration updates into a delta state machine (DSM) and unveil two types of dependent misconfigurations among states (inter-state) and within a state (intra-state); They stem from structural dependency and cross-parameter dependency. We further show that such misconfigurations incur service disruption and performance degradation. Our findings have been largely validated with three US operators and one Chinese operator; Our study has uncovered 644 instances of problematic dependencies.

https://dl.acm.org/doi/pdf/10.1145/3595288

Dependent Misconfigurations in 5G/4.5G Radio Resource Control

Fifth-generation (5G) networks are now in a stable phase in terms of commercial release. 5G design is flexible to support a diverse range of radio bands (i.e., low-, mid-, and high-band) and application requirements. Since its initial roll-out in 2019, extensive measurements studies have revealed key aspects of commercial 5G deployments (e.g., coverage, signal strength, throughput, latency, handover, and power consumption among others) for several scenarios (e.g., pedestrian and car mobility, mid-, and high-bands, etc.). In this paper, we make a twofold contribution. First, we carry out an in-depth measurement study of 5G in a large public bus transit system in a major European city. Second, based on the insights observed with the measurement study, we propose a new target cell selection criteria applicable to Fast Conditional Handover (FCHO), a 3GPP-specific 5G technique to foster reliable mobility. Our results are based on an extensive measurement campaign performed with several mobile phones connected to several mobile network operators totaling more than 1500 km over three months. The measurements reveal how flexible the network deployment is by analyzing Radio Resource Control (RRC) messages, mobility management and the suitability of our FCHO solution, and application performance. 

A study on 5G performance and fast conditional handover for public transit systems

Roaming provides users with voice and data connectivity when traveling abroad. This is particularly the case in Europe where the "Roam like Home" policy established by the European Union in 2017 has made roaming affordable. Nonetheless, due to various policies employed by operators, roaming can incur considerable performance penalties as shown in past studies of 3G/4G networks. As 5G provides significantly higher bandwidth, how does roaming affect user-perceived performance? We present, to the best of our knowledge, the first comprehensive and comparative measurement study of commercial 5G in four European countries.Our measurement study is unique in the way it makes it possible to link key 5G mid-band channels and configuration parameters ("policies") used by various operators in these countries with their effect on the observed 5G performance from the network (in particular, the physical and MAC layers) and applications perspectives. Our measurement study not only portrays users’ observed quality of experience when roaming, but also provides guidance to optimize the network configuration and to users and application developers in choosing mobile operators. Moreover, our contribution provides the research community with the largest cross-country roaming 5G dataset to stimulate further research.

Roaming across the European Union in the 5G Era: Performance, Challenges, and Opportunities

—This paper reports our in-depth measurement study of 5G experience with three US operators (AT&T, Verizon and T-Mobile). We not only quantitively characterize 5G coverage, availability and performance (over both mmWave and Sub-6GHz bands), but also identify several performance issues and analyze their root causes. We see that real 5G experience is not that satisfactory as anticipated. It is mainly because faster 5G is not used as it can and should. We have several surprising ﬁndings: Despite huge speed potentials (say, up to several hundreds of Mbps), more than half are not realized in practice; Such under-utilization is mainly stemmed from current practice and policies that manage radio resource in a performance-oblivious manner; 5G is even less used where 5G is co-deployed over both mmWave and Sub-6GHz bands; Transiently missing 5G is not uncommon and its negative impacts last much longer. Inspired by our ﬁndings, we design a patch solution called 5GBoost to ﬁx the problems identiﬁed in legacy 5G operations. Our preliminary evaluation validates its effectiveness to realize more 5G potentials.

A Close Look at 5G in the Wild: Unrealized Potentials and Implications

Cellular networks that offer ubiquitous connectivity have been the major medium for delivering emergency services. In the U.S., mobile users can dial an emergency call with 911 for emergency uses in cellular networks, and the call can be forwarded to public safety answer points (PSAPs), which deal with emergency service requests. According to regulatory authority requirements for the cellular emergency services, anonymous user equipment (UE), which does not have a SIM (Subscriber Identity Module) card or a valid mobile subscription, is allowed to access them. Such support of emergency services for anonymous UEs requires different operations from conventional cellular services, and can therefore increase the attack surface of the cellular infrastructure. In this work, we are thus motivated to study the insecurity of the cellular emergency services and then discover four security vulnerabilities from them. Threateningly, they can be exploited to launch not only free data service attacks against cellular carriers, but also data DoS/overcharge and denial of cellular emergency service (DoCES) attacks against mobile users. All vulnerabilities and attacks have been validated experimentally as practical security issues in the networks of three major U.S. carriers. We finally propose and prototype standard-compliant remedies to mitigate the vulnerabilities.

Uncovering insecure designs of cellular emergency services (911)

Carrier aggregation (CA) is an important component technology in 5G and beyond. It aggregates multiple spectrum fragments to serve a mobile device. However, the current CA suffers under both high mobility and increased spectrum space. The limitations are rooted in its sequential, cell-by-cell operations. In this work, we propose CA++, which departs from the current paradigm and explores a group-based design scheme. We thus propose new algorithms that enable concurrent channel inference by measuring one or few cells but inferring all, while minimizing measurement cost via set cover approximations. Our evaluations have confirmed the effectiveness of CA++. Our solution can also be adapted to fit in the current 5G OFDM PHY and the 3GPP framework.

CA++: Enhancing Carrier Aggregation Beyond 5G

The cellular network offers a ubiquitous emergency call service with its pervasive coverage. In the United States, it can be consumed by dialing 911 for cellular users, and the emergency call is forwarded to the public safety answer point (PSAP), which handles emergency service requests. According to regulatory authority requirements [1,2,3] for cellular emergency services, anonymous user equipment (UE) is allowed to access them without a SIM (Subscriber Identity Module) card, a valid mobile subscription, or a roaming agreement with the visited cellular network. Such support of the cellular emergency services requires different operations from conventional cellular services, thereby increasing the attack surface of the cellular infrastructure.

Unveiling the Insecurity of Operational Cellular Emergency Services (911): Vulnerabilities, Attacks, and Countermeasures

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