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1. Enabling Opportunistic Low-cost Smart Cities By Using Tactical Edge Node Placement

   https://doi.org/10.23919/WONS51326.2021.9415579  

   Madamori, Oluwashina; Max-Onakpoya, Esther; Erhardt, Gregory D.; Baker, Corey E. (January 2021, 2021 16th Annual Conference on Wireless On-demand Network Systems and Services Conference (WONS))

   null (Ed.)

   Smart city projects aim to enhance the management of city infrastructure by enabling government entities to monitor, control and maintain infrastructure efficiently through the deployment of Internet-of-things (IoT) devices. However, the financial burden associated with smart city projects is a detriment to prospective smart cities. A noteworthy factor that impacts the cost and sustainability of smart city projects is providing cellular Internet connectivity to IoT devices. In response to this problem, this paper explores the use of public transportation network nodes and mules, such as bus-stops as buses, to facilitate connectivity via device-to-device communication in order to reduce cellular connectivity costs within a smart city. The data mules convey non-urgent data from IoT devices to edge computing hardware, where data can be processed or sent to the cloud. Consequently, this paper focuses on edge node placement in smart cities that opportunistically leverage public transit networks for reducing reliance on and thus costs of cellular connectivity. We introduce an algorithm that selects a set of edge nodes that provides maximal sensor coverage and explore another that selects a set of edge nodes that provide minimal delivery delay within a budget. The algorithms are evaluated for two public transit network data-sets: Chapel Hill, North Carolina and Louisville, Kentucky. Results show that our algorithms consistently outperform edge node placement strategies that rely on traditional centrality metrics (betweenness and in-degree centrality) by over 77% reduction in coverage budget and over 20 minutes reduction in latency. 

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2. dAuth: A Resilient Authentication Architecture for Federated Private Cellular Networks

   https://doi.org/10.1145/3651890.3672263  

   Johnson, Matthew; Singanamalla, Sudheesh; Durand, Nick; Jang, Esther_Han Boel; Sevilla, Spencer; Heimerl, Kurtis (August 2024, ACM)

   We present dAuth, an approach to device authentication in private cellular networks which refactors the responsibilities of authentication to enable multiple small private cellular networks to federate together to provide a more reliable and resilient service than could be achieved on their own. dAuth is designed to be backwards compatible with off-the-shelf 4G and 5G cellular devices and can be incrementally deployed today. It uses cryptographic secret sharing and a division of concerns between sensitive data stored with backup networks and non-sensitive public directory data to securely scale authentication across multiple redundant nodes operating among different and untrusted organizations. Specifically, it allows a collection of pre-configured backup networks to authenticate users on behalf of their home network while the home network is unavailable. We evaluate dAuth’s performance with production equipment from an active federated community network, finding that it is able to work with existing systems. We follow this with an evaluation using a simulated 5G RAN and find that it performs comparably to a standalone cloud-based 5G core at low load, and outperforms a centralized core at high load due to its innate load-sharing properties. 

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3. Multi-Modal Vehicle Data Delivery via Commercial 5G Mobile Networks: An Initial Study

   https://doi.org/10.1109/ICDCSW60045.2023.00026  

   Carpenter, Jason; Ye, Wei; Qian, Feng; Zhang, Zhi-Li (July 2023, 2023 IEEE 43rd International Conference on Distributed Computing Systems Workshops (ICDCSW))

   Support for connected and autonomous vehicles (CAVs) is a major use case of 5G networks. Due to their large from factors, CAVs can be equipped with multiple radio antennas, cameras, LiDAR and other sensors. In other words, they are "giant" mobile integrated communications and sensing devices. The data collected can not only facilitate edge-assisted autonomous driving, but also enable intelligent radio resource allocation by cellular networks. In this paper we conduct an initial study to assess the feasibility of delivering multi-modal sensory data collected by vehicles over emerging commercial 5G networks. We carried out an "in-the-wild" drive test and data collection campaign between Minneapolis and Chicago using a vehicle equipped with a 360° camera, a LiDAR device, multiple smart phones and a professional 5G network measurement tool. Using the collected multi-modal data, we conduct trace-driven experiments in a local streaming testbed to analyze the requirements and performance of streaming multi-modal sensor data over existing 4G/5G networks. We reveal several notable findings and point out future research directions. 

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4. Reliable edge-to-core optical networks: An optimal algorithm for maximal path diversity

   https://doi.org/10.1016/j.comnet.2024.110268  

   Shakeri, Ali; Zhang, Tianliang; Ramanathan, Shunmugapriya; Razo, Miguel; Tacca, Marco; Fumagalli, Andrea (April 2024, Computer Networks)

   With the emergence of IoT applications, 5G, and edge computing, network resource allocation has shifted toward the edge, bringing services closer to the end users. These applications often require communication with the core network for purposes that include cloud storage, compute offloading, 5G-and-Beyond transport communication between centralized unit (CU), distributed unit (DU) and core network, centralized network monitoring and management, etc. As the number of these services increases, efficient and reliable connectivity between the edge and core networks is of the essence. Wavelength Division Multiplexing (WDM) is a well-suited technology for transferring large amounts of data by simultaneously transmitting several wavelength-multiplexed data streams over each single fiber optics link. WDM is the technology of choice in mid-haul and long-haul transmission networks, including edge-to-core networks, to offer increased transport capacity. Optical networks are prone to failures of components such as network fiber links, sites, and transmission ports. A single network element failure alone can cause significant traffic loss due to the disruption of many active data flows. Thus, fault-tolerant and reliable network designs remain a priority. The architecture called “dual-hub and dual-spoke” is often used in metro area networks (MANs). A dual-hub, or in general a multi-hub network, consists of a set of designated destination nodes (hubs) in which the data traffic from all other nodes (the peripherals) should be directed to the hubs. Multiple hubs offer redundant connectivity to and from the core or wide area network (WAN) through geographical diversity. The routing of the connections (also known as lightpaths) between the peripheral node and the hubs has to be carefully computed to maximize path diversity across the edge-to-core network. This means that whenever possible the established redundant lightpaths must not contain a common Shared Risk Link Group (SRLG). An algorithm is proposed to compute the most reliable set of SRLG disjoint shortest paths from any peripheral to all hubs. The proposed algorithm can also be used to evaluate the overall edge-to-core network reliability quantified through a newly introduced figure of merit. 

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5. An REU/RET Project: IoT Platform and Network Data Visualization

   Toutsop, O. (November 2021, 2021 Fall ASEE Middle Atlantic Section Meeting)

   Internet of Things (IoT) is a connected network of devices that exchange data using different protocols. The application of IoT ranges from intelligent TVs and intelligent Refrigerators to smart Transportation. This research aims to provide students with hands-on training on how to develop an IoT platform that supports device management, connectivity, and data management. People tend to build interconnected devices without having a basic understanding of how the IoT platform backend function. Studying the Arm Pelion will help to understand how IoT devices operate under the hood. This past summer, Morgan State University has hosted undergraduate engineering students and high school STEM teachers to conduct IoT security research in the Cybersecurity Assurance & Policy (CAP) Center. The research project involved integrating various hardware sensor devices and real-time data monitoring using the Arm Pelion IoT development platform. Some of the student/teacher outcomes from the project include: 1) Learning about IoT Technology and security; 2) Programming an embedded system using Arm Mbed development board and IDE; 3 3) Developing a network of connected IoT devices using different protocols such as LWM2M, MQTT, CoAP; 4) Investigating the cybersecurity risks associated with the platform; and 5) Using data analysis and visualization to understand the network data and packet flow. First, the student/teacher must consider the IoT framework to understand how to address the security. The IoT framework describes the essential functions of an IoT network, breaking it down into separate layers. These layers include an application layer, middleware layer, and connectivity layer. The application layer allows the users to access the platform via a smartphone or any other dashboard. The Middleware layer represents the backend system that provides edge devices with data management, messaging, application services, and authentication. Finally, the connectivity layer includes devices that connect the user to the network, including Bluetooth or WiFi. The platform consists of several commercial IoT devices such as a smart camera, baby monitor, smart light, and other devices. We then create algorithms to classify the network data flow; to visualize the packets flow in the network and the structure of the packets data frame over time. 

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