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1. Design patterns for the industrial Internet of Things

   https://doi.org/10.1109/WFCS.2018.8402353  

   Bloom, Gedare; Alsulami, Bassma; Nwafor, Ebelechukwu; Bertolotti, Ivan Cibrario (June 2018, 2018 14th IEEE International Workshop on Factory Communication Systems (WFCS))

   The Internet of Things (IoT) is a vast collection of interconnected sensors, devices, and services that share data and information over the Internet with the objective of leveraging multiple information sources to optimize related systems. The technologies associated with the IoT have significantly improved the quality of many existing applications by reducing costs, improving functionality, increasing access to resources, and enhancing automation. The adoption of IoT by industries has led to the next industrial revolution: Industry 4.0. The rise of the Industrial IoT (IIoT) promises to enhance factory management, process optimization, worker safety, and more. However, the rollout of the IIoT is not without significant issues, and many of these act as major barriers that prevent fully achieving the vision of Industry 4.0. One major area of concern is the security and privacy of the massive datasets that are captured and stored, which may leak information about intellectual property, trade secrets, and other competitive knowledge. As a way forward toward solving security and privacy concerns, we aim in this paper to identify common input-output (I/O) design patterns that exist in applications of the IIoT. These design patterns enable constructing an abstract model representation of data flow semantics used by such applications, and therefore better understand how to secure the information related to IIoT operations. In this paper, we describe communication protocols and identify common I/O design patterns for IIoT applications with an emphasis on data flow in edge devices, which, in the industrial control system (ICS) setting, are most often involved in process control or monitoring. 

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2. Actor-Critic Network for O-RAN Resource Allocation: xApp Design, Deployment, and Analysis

   https://doi.org/10.1109/GCWkshps56602.2022.10008713  

   Kouchaki, Mohammadreza; Marojevic, Vuk (December 2022, 2022 IEEE Globecom Workshops (GC Wkshps))

   Open Radio Access Network (O-RAN) has introduced an emerging RAN architecture that enables openness, intelligence, and automated control. The RAN Intelligent Controller (RIC) provides the platform to design and deploy network controllers. xApps are the applications that can leverage machine learning (ML) algorithms for near-real time control. Despite the opportunities provided by this new architecture, the progress of practical artificial intelligence (AI)-based solutions for network control and automation has been slow. There is a lack of end-to-end solutions for designing, deploying, and testing AI-based xApps in production-like network settings. This paper introduces an end-to-end O-RAN design and evaluation procedure using the latest O-RAN architecture and interface releases. We provide details on the development of a reinforcement learning (RL)-based xApp, considering two RL approaches and present numerical results to validate the xApp. 

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3. Demo Abstract: A Full-Blown 6TiSCH Network with Partition-based Resource Management for Large-Scale Real-Time Wireless Applications

   https://doi.org/10.1109/RTAS52030.2021.00067  

   Wang, Jiachen; Zhang, Tianyu; Han, Song; Hu, Xiaobo Sharon (May 2021, 2021 IEEE 27th Real-Time and Embedded Technology and Applications Symposium (RTAS))

   null (Ed.)

   Industrial Internet of Things (IIoT) systems aim to interconnect a large number of heterogeneous industrial sensing and actuation devices through both wired and wireless communication technologies and further connect them to the Internet to achieve ubiquitous sensing, computing and control services [1]. As a representative IIoT technology, 6TiSCH [2] targets at gluing together the 802.15.4e data link layer (offering industrial performance in terms of timing, reliability and power consumption) and an IP-enabled upper layer stack to achieve both deterministic network performance and seamless integration with Internet services. In recent years, 6TiSCH has been receiving increasing attentions from both industry and academia. We have witnessed its wide deployment in many industrial domains, including advanced manufacturing, industrial process control, smart grids, and healthcare. 

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4. Toward Next Generation Open Radio Access Networks--What O-RAN Can and Cannot Do!

   https://doi.org/10.1109/MNET.108.2100659  

   Abdalla, Aly S.; Upadhyaya, Pratheek S.; Shah, Vijay K.; Marojevic, Vuk (July 2022, IEEE Network)

   The open radio access network (O-RAN) describes an industry-driven open architecture and interfaces for building next generation RANs with artificial intelligence (AI) controllers. We circulated a survey among researchers, developers, and practitioners to gather their perspectives on O-RAN as a framework for 6G wireless research and development (R&D). The majority responded in favor of O-RAN and identified R&D of interest to them. Motivated by these responses, this paper identifies the limitations of the current O-RAN specifications and the technologies for overcoming them. We recognize end-to-end security, deterministic latency, physical layer real-time control, and testing of AI-based RAN control applications as the critical features to enable and discuss R&D opportunities for extending the architectural capabilities of O-RAN as a platform for 6G wireless. 

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5. 3D-O-RAN: Dynamic Data Driven Open Radio Access Network Systems

   https://doi.org/10.1109/MILCOM55135.2022.10017706  

   Restuccia, Francesco; Blasch, Erik; Ashdown, Andrew; Ashdown, Jonathan; Turck, Kurt (November 2022, MILCOM 2022 - 2022 IEEE Military Communications Conference (MILCOM))

   This position paper introduces a Dynamic Data Driven Open Radio Access Network System (3D-O-RAN). The key objective of 3D-O-RAN is to support congested, contested and contaminated tactical settings where multimedia sensors, application constraints and operating wireless conditions may frequently change over space, time and frequency. 3D-O-RAN is compliant with the O-RAN specification for beyond 5G cellular systems to reduce costs and guarantee interoperability among vendors. Moreover, 3D-O-RAN integrates computational, sensing, and cellular networking components in a highly-dynamic, feedback-based, data-driven control loop. Specifically, 3D-O-RAN is designed to incorporate heterogeneous data into the network control loop to achieve a system-wide optimal operating point. Moreover, 3D-O-RAN steers the multimedia sensor measurement process in real time according to the required application needs and current physical and/or environmental constraints. 3D-O-RAN uses (i) a semantic slicing engine, which takes into account the semantic of the application to optimally compress the multimedia stream without losing in classification accuracy; (ii) a dynamic data driven neural network certification system that translates mission-level constraints into technical-level constraints on neural network latency/accuracy, and occupation of hardware/software resources. Realistic use-case scenarios of 3D-O-RAN in a tactical context demonstrate system performance. 

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