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IEEE Networking Letters 2025年

作者： Li, Kai Liang, Yilei Yuan, Xin Ni, Wei Crowcroft, Jon Yuen, Chau Akan, Ozgur B. Group Department of Engineering University of Cambridge CambridgeCB3 0FA United Kingdom Real-Time and Embedded Computing Systems Research Centre CISTER Porto4249-015 Portugal The Department of Computer Science and Technology University of Cambridge CambridgeCB3 0FA United Kingdom Commonwealth Scientific and Industrial Research Organization CSIRO SydneyNSW2122 Australia The School of Computing Science and Engineering University of New South Wales Australia Nanyang Technological University SG 639798 Singapore Group Division of Electrical Engineering Department of Engineering University of Cambridge CambridgeCB3 0FA United Kingdom The Center for neXt-generation Communications CXC Koç University Istanbul34450 Turkey

This letter puts forth a new hybrid horizontal-vertical federated learning (HoVeFL) for mobile edge computing-enabled Internet of Things (EdgeIoT). In this framework, certain EdgeIoT devices train local models using the same data samples but analyze disparate data features, while the others focus on the same features using non-independent and identically distributed (non-IID) data samples. Thus, even though the data features are consistent, the data samples vary across devices. The proposed HoVeFL formulates the training of local and global models to minimize the global loss function. Performance evaluations on CIFAR-10 and SVHN datasets reveal that the testing loss of HoVeFL with 12 horizontal FL devices and six vertical FL devices is 5.5% and 25.2% higher, respectively, compared to a setup with six horizontal FL devices and 12 vertical FL devices. © 2019 IEEE.

关键词： Federated learning

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Secure wireless avionics intra-communications: The SCOTT approach

Ada User Journal

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Ada User Journal 2018年第4期39卷 267-276页

作者： Samano-Robles, Ramiro Neves, José Research Centre in Real-time and Embedded Computing Systems Porto Portugal GMVIS SKYSOFTSA Lisbon Portugal

This paper presents the objectives and architecture of the use case of secure wireless avionics intracommunications of the European Project SCOTT (secure connected trustable things). SCOTT aims to build trust of the Internet of Things (IoT) in industrial applications. SCOTT addresses multiple issues such as security, safety, privacy, and dependability across 5 industrial domains: automotive, aeronautics, railway, building and healthcare. The aeronautics use case focuses on the application for active flow control (AFC) based on dense wireless sensor and actuator networks (DWSANs). Topics about security, vulnerabilities and safety in the general field of wireless avionics intra-communications (WAICs) will be addressed. The paper presents preliminary conclusions of the vulnerabilities and security solutions across different entities and layers of the aeronautics IoT architecture. © 2018 *** rights reserved.

关键词： Internet of things

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Artificial Intelligence for Wireless Communications: The InSecTT perspective

IEEE Open Journal of the Industrial Electronics Society

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IEEE Open Journal of the Industrial Electronics Society 2025年

作者： Robles, Ramiro Samano Javanmardi, Gowhar Pilz, Christoph Kwapisiewicz, Przemyslaw Rzymowski, Mateusz Kulas, Lukasz Davoli, Luca Belli, Laura Ferrari, Gianluigi Wenning, Bernd-Ludwig Gonca, Bugra Prasad, R. Venkatesha Simha, Ashutosh Kiviranta, Markku Moilanen, Ilkka Robinson, Sean Cirill, Gennaro Soyturk, Mujdat Bostanci, Yavuz Selim Hormann, Leander B. Research Centre in Real-time and Embedded Computing Systems Porto Portugal University of Porto Faculty of Engineering Portugal Virtual Vehicle Research GmbH Graz Austria Gdansk University of Technology Poland Lab Department of Engineering and Architecture Parma Italy Rome Italy Munster Technological University Cork Ireland NuRD Innovation Center Turkey Technical University of Delft Netherlands VTT Research Corporation Finland F-Secure Corporation Finland Marmara University Istanbul Turkey 1Linz Center of Mechatronics GmbH Linz Austria

This paper presents an overview of how Artificial Intelligence (AI) and edge technology have been used to improve wireless connectivity in multiple industrial Use Cases (UCs) of the EU project "Intelligent Secure Trustable Things"(InSecTT). We present a brief introduction of the InSecTT framework for crossdomain architecture design, which targets UCs assisted by reusable and-or interoperable technical Building Blocks (BBs). These BBs constitute the construction bricks containing AI and supporting components that were used to build different UCs. The framework consists of multiple stages based on the processing of UC-BB requirements (RQs). These stages include: i) collection, ii) harmonization, iii) refinement, iv) classification, v) architecture alignment, and vi) functionality modeling of RQs. The most relevant results of these stages are discussed here, with emphasis on the need for a refined granularity of technical components with common functionalities named sub-building blocks (SBBs), where collaboration and cross-domain reusability were optimized. The design process shed light on how AI and SBBs were implemented across different layers and entities of our reference architecture for the Internet-of-Things (IoT), including the interfaces used for information exchange. This detailed interface analysis is expected to reveal issues such as bottlenecks, constraints, vulnerabilities, scalability problems, security threats, etc. This will, in turn, contribute to identifying design gaps in AI-enabled IoT systems. The paper summarizes the SBBs related to wireless connectivity, including a general description, implementation issues, comparison of results, adopted interfaces, and conclusions across domains. © 2020 IEEE.

关键词： Reusability

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Cooperative Vehicle Platoon Intra-communications over Space-time Correlated Rice fading Channels with co-channel Interference 7

Cooperative Vehicle Platoon Intra-communications over Space-...

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7th IEEE World Forum on Internet of Things, WF-IoT 2021

作者： Samano-Robles, Ramiro Research Centre in Real-time and Embedded Computing Systems Porto Portugal

ISBN: (纸本)9781665444316

This paper investigates the performance of vehicle platoon intra-communications in the presence of node relaying cooperation. In the proposed scenario, all nodes are allowed to relay the signals of other entities towards the next/final destination. This improves channel conditions by mimicking large scale (virtual) antennas, thereby achieving the concept of cooperative diversity. The scenario considers a platoon of J vehicles assisted by a set of relay nodes. These potential relays include the same vehicles of the platoon, as well as base stations (BSs) and/or road-side units (RSUs). The objective is to evaluate the delay experienced by a packet transmitted by the leader towards all the vehicles of the formation. Each vehicle and each relayingable node is considered to relay the correctly received message to the remaining entities, but most importantly to all the vehicles of the platoon. We consider that if a given transmission attempt is not successfully received by all entities, then the transmitter and relays with a correct copy of the transmission engage in a persistent retransmission scheme that stops only when the packet has been correctly received by all the vehicles. Instantaneous and ideal feedback is used in all calculations. The criterion used to consider a packet correctly received by the destination is that the instantaneous signal-to-interference-plus-noise ratio (SINR) surpasses a reception threshold. It is assumed that the destination nodes store a copy of all the received transmissions over consecutive time slots and antenna elements. These signals are processed using ideal maximum-ratio combining (MRC) to obtain a more reliable copy of the information (i.e. using time and/or retransmission diversity). Multiple antennas are used by all the vehicles and nodes of the network under analysis. Novel spatial and temporal correlation tools are introduced in the channel model with Rice fading statistics and co-channel interference. Results suggest that RSUs

关键词： Fading channels

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MAC-PRY cross-layer design for secure wireless avionics intra-communications 8

MAC-PRY cross-layer design for secure wireless avionics intr...

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8th International Conference on Emerging Security Technologies, EST 2019

作者： Samano-Robles, Ramiro Research Centre in Real-time and Embedded Computing Systems Porto Portugal

ISBN: (纸本)9781728155463

This paper presents a framework for medium access control (MAC) and physical (PRY) cross-layer security design of wireless avionics intra-communications (WAICs). The paper explores the different options based on the latest results of MAC-PRY cross-layer design and the available standard technologies for WAICs. Particular emphasis is given to solutions based on multiple-input multiple-output (MIMO) systems and recent developments towards a wireless technology with ultra-low latency and high reliability in the context of 5G and machine-type traffic support. One major objective is to improve WAICs technology and thus match the real-time, reliability and safety critical performance of the internal aeronautics bus technologies (e.g., ARINC 664). The main identified vulnerabilities and potential solutions are explored, as well as their impact on system design complexity and feasibility for wireless networks on-board aircraft. The solutions are presented in the context of the European project SCOTT (secure connected trustable things) using the recently released reference architecture for trusted IoT systems. Other aspects of SCOTT such as trust, privacy, security classes, and safety are also discussed here for the aeronautics domain. © 2019 IEEE.

关键词： Medium access control

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Employing Intelligent Aerial Data Aggregators for the Internet of Things: Challenges and Solutions

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IEEE Internet of Things Magazine 2022年第1期5卷 136-141页

作者： Li, Kai Ni, Wei Noor, Alam Guizani, Mohsen Real-Time and Embedded Computing Systems Research Centre Portugal Commonwealth Scientific and Industrial Research Organization Digital Productivity and Services Flagship Australia Qatar University Qatar

Internet-of-Things (IoT) devices equipped with temperature and humidity sensors and cameras are increasingly deployed to monitor remote and human-unfriendly areas (e.g., farmlands, forests, rural highways, and electricity infrastructures). Aerial data aggregators such as autonomous drones provide a promising solution for collecting sensory data of IoT devices in human-unfriendly environments, enhancing network scalability and connectivity. The flexibility of a drone and favorable line-of-sight connection between the drone and IoT devices can be exploited to improve data reception at the drone. This article first discusses challenges of the drone-assisted data aggregation in IoT networks, such as incomplete network knowledge at the drone, limited buffers of the IoT devices, and lossy wireless channels. Next, we investigate the feasibility of onboard deep-reinforcement-learning-based solutions to allow a drone to learn its cruise control and data collection schedule online. For deep reinforcement learning in a continuous operation domain, deep deterministic policy gradient (DDPG) is suitable to deliver effective joint cruise control and communication decision, using its outdated knowledge of the IoT devices and network states. A case study shows that the DDPG-based framework can take advantage of the continuous actions to substantially outperform existing non-learning-based alternatives. © 2018 IEEE.

关键词： Drones

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LEM: a Tool for Large-Scale Workflow Control in Edge-Based Industry 5.0 Applications 19

LEM: a Tool for Large-Scale Workflow Control in Edge-Based I...

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19th Annual International Conference on Distributed computing in Smart systems and the Internet of Things, DCOSS-IoT 2023

作者： Reis, Rui Santos, Pedro M. Sousa, Mario J. Martins, Nuno Sousa, Joana Almeida, Luis Universidade Do Porto Faculdade de Engenharia Portugal Portugal Cister Research Center in Real-Time and Embedded Computing Systems Portugal

ISBN: (纸本)9798350346497

Edge computing is poised to greatly boost Industry 5.0 by providing a computing substrate that can run highly specialized applications with minimal latency, reducing the requirements on computational resources at the end-user and allowing the sharing of resources between multiple end-users. The intended services and workflows need to be designed, configured and deployed at target edge devices, and during operation their status needs to be monitored. There are several industrial frameworks that provide such functionalities, but often there is little support to execute them simultaneously over many target devices. In this paper we present the LEM tool, a tool that enables the management (monitor, configure, deploy) of workflows in a large number of edge devices. The tool connects to existing industrial frameworks to provide these functionalities, abstracting the low level configuration aspects of each framework and enabling simultaneous configuration of multiple devices, a feature that many frameworks do not support. The tool offers a web-based GUI that allows the infrastructure manager to conveniently check the status of all devices and flows running in each device, deploy new flows on selected devices, and start and stop flows. Experimental measurements show residual response time overhead as the number of devices increases. © 2023 IEEE.

关键词： edge Industry5.0 Node-RED workflow

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Special Issue on Nanopackaging: Part II

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IEEE NANOTECHNOLOGY MAGAZINE 2019年第1期13卷 3-3页

作者： Yeow, John T. W. Real-Time and Embedded Computing Systems Research Centre (CISTER) Porto Portugal

Presents the introductory editorial for this issue of the publication.

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Work-In-Progress: a DSL for the safe deployment of Runtime Monitors in Cyber-Physical systems

Work-In-Progress: a DSL for the safe deployment of Runtime M...

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real-time systems Symposium (RTSS)

作者： Giann Spilere Nandi David Pereira José Proença Eduardo Tovar CISTER - Research Centre in Real-Time & Embedded Computing Systems Portugal

ISBN: (数字)9781728183244

ISBN: (纸本)9781728183251

Guaranteeing that safety-critical Cyber-Physical systems (CPS) do not fail upon deployment is becoming an even more complicated task with the increased use of complex software solutions. To aid in this matter, formal methods (rigorous mathematical and logical techniques) can be used to obtain proofs about the correctness of CPS. In such a context, Runtime Verification has emerged as a promising solution that combines the formal specification of properties to be validated and monitors that perform these validations during runtime. Although helpful, runtime verification solutions introduce an inevitable overhead in the system, which can disrupt its correct functioning if not safely employed. We propose the creation of a Domain Specific Language (DSL) that, given a generic CPS, 1) verifies if its real- time scheduling is guaranteed, even in the presence of coupled monitors, and 2) implements several verification conditions for the correct-by-construction generation of monitoring architectures. To achieve it, we plan to perform statical verifications, derived from the available literature on schedulability analysis, and powered by a set of semi-automatic formal verification tools.

关键词： Runtime Tools Cyber-physical systems Safety DSL Proposals Monitoring

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Comparing Performance of Machine Learning Tools Across computing Platforms 18

Comparing Performance of Machine Learning Tools Across Compu...

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18th Conference on Computer Science and Intelligence systems, FedCSIS 2023

作者： Vicente, Pedro Santos, Pedro M. Asulba, Barikisu Martins, Nuno Sousa, Joana Almeida, Luis Portugal Universidade Do Porto Faculdade de Engenharia Portugal Cister Research Center in Real-Time and Embedded Computing Systems Portugal Nos Inovacao Portugal

ISBN: (纸本)9788396744784

embedded systems (ES) are wide-spread in our world and responsible for many critical systems. More recently, machine learning (ML) tools have become a well-established solution for data-intensive tasks, but their application in embedded systems is still gaining traction and their real-time performance is often unclear. We provide a (non-extensive) review of the ML tools that may be suited for deployment in ES, from which we selected two representative tools - the well-established Python-based Scikit-Learn, and the interoperability-oriented ONNX Runtime - to compare their response time. Using archetypal datasets and four pre-trained ML models, we measure the prediction time for each sample, for each model, in Scikit-Learn and ONNX Runtime in a standard desktop (to compare performance of the tools in the same platform), and for ONNX Runtime in a representative ES, a Raspberry Pi v4 (to compare performance of the same tool across platforms). We report that ONNX considerably improves over Scikit-Learn, and experiences a negligible performance degradation when ported to the RPi. © 2023 Polish Information Processing Society.

关键词： embedded systems

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