Search Results (33)

Solar-powered pumping systems using series pumps are commonly applied in the delivery of water to remote agricultural regions, particularly in hilly tropical terrain. The synchronization of these pumps typically depends on reliable communication; however, dense vegetation, elevation changes, and weather conditions often disrupt signals. To address these limitations, a fully decentralized, communication-free control system is proposed. Each pumping station operates independently while maintaining synchronized operation through emulated neighbor sensing. The system applies a discrete-time control algorithm with virtual sensing that estimates neighboring pump statuses. Each station consists of a solar photovoltaic (PV) array, variable-speed drive, variable inlet valve, reserve tank, and local control unit. The controller adjusts the valve positions and pump power based on real-time water level measurements and virtual neighbor sensing. The simulation results across four scenarios, including clear sky, cloudy conditions, temporary outage, and varied irradiance, demonstrated steady-state operation with no water overflow or shortage and a steady-state error less than 4% for 3 m³ transfer. The error decreased as the average power increased. The proposed method maintained system functionality under simulated power outage and variable irradiance, confirming its suitability for remote agricultural areas where communication infrastructure is limited. Full article

This paper investigates the virtualization of LoRaWAN end nodes through Linux containers (LXCs) to improve scalability, flexibility, and resource management. By leveraging lightweight Docker-based virtualization, we break down the core functions of the LoRaWAN node, comprising the application, LoRaWAN, and LoRa layers, into modular containers. In this work, a fully virtualized end node is demonstrated. The obtainable performance is not only compared against the standard approach that leverages a LoRaWAN-compliant module but also against an emulated solution that mimics the desired functionalities purely in software. A controlled, uniform testbed, exploiting the capability of a virtual machine hypervisor to change the way the underlying hardware is abstracted to guest environments, is considered. Key metrics, including resource utilization and latency, are explicitly defined and evaluated. The results underscore the potential of container technologies to transform the deployment and management of communication solutions targeting Internet-of-Things (IoT) scenarios not only for the infrastructure but also for end devices, with implications for future advancements in wireless network virtualization. Full article

The transition to inverter-dominated power systems with novel control strategies has created weak grid scenarios, prompting extensive research into grid-forming (GFM) converters and advanced GFM control schemes. This study evaluates two GFM control strategies for their stabilizing effects in weakly interconnected and islanded power systems: the established Virtual Synchronous Machine (VSM) control and the newly developed Phase-Restoring Principle (PRP). The evaluation is conducted using a real-time electromagnetic transient (EMT) simulation testbed with Hardware-in-the-Loop (HiL) capabilities. The system includes a multi-terminal medium-voltage (MVDC) and high-voltage direct current (HVDC) network weakly coupled to a network equivalent, represented by a scaled synchronous machine (SynM) to replicate grid inertia. Modular multilevel converters (MMCs) model the converters, while Power Hardware-in-the-Loop (PHiL) experiments integrate real power hardware. Dynamic interactions, including islanded conditions, are emulated to assess the performance of GFM controls and their interactions in HV/MV and AC/DC systems. The results demonstrate the compatibility of diverse GFM schemes with grid-following controls and synchronous machines, emphasizing their positive contributions to system stability. This modular demonstrator, as a realistic prototype of future power systems, provides a flexible platform for testing emerging GFM strategies and hardware, supporting the development of robust and stable inverter-based grids. Full article

The convergence of IT and OT networks has gained significant attention in recent years, facilitated by the increase in distributed computing capabilities, the widespread deployment of Internet of Things devices, and the adoption of Industrial Internet of Things. This convergence has led to a drastic increase in external access capabilities to previously air-gapped industrial systems for process control and monitoring. To meet the need for remote access to system information, protocols designed for the OT space were extended to allow IT networked communications. However, OT protocols often lack the rigor of cybersecurity capabilities that have become a critical characteristic of IT protocols. Furthermore, OT protocol implementations on individual devices can vary in performance, requiring the comprehensive evaluation of a device’s reliability and capabilities before installation into a critical infrastructure production network. In this paper, the authors define a framework for identifying vulnerabilities within these protocols and their on-device implementations, utilizing formal modeling, hardware in the loop-driven network emulation, and fully virtual network scenario simulation. Initially, protocol specifications are modeled to identify any vulnerable states within the protocol, leveraging the Construction and Analysis of Distributed Processes (CADP) software (version 2022-d “Kista”, which was created by Inria, the French Institute for Research in Computer Science and Automation, in France). Device characteristics are then extracted through automated real-time network emulation tests built on the OMNET++ framework, and all measured device characteristics are then used as a virtual device representation for network simulation tests within the OMNET++ software (version 6.0.1., a public-soucre, open-architecture software, initially developed by OpenSim Limited in Budapest, Hungary), to verify the presence of any potential vulnerabilities identified in the formal modeling stage. With this framework, the authors have thus defined an end-to-end process to identify and verify the presence and impact of potential vulnerabilities within a protocol, as shown by the presented results. Furthermore, this framework can test protocol compliance, performance, and security in a controlled environment before deploying devices in live production networks and addressing cybersecurity concerns. Full article

Forest fires are among the most devastating natural disasters, causing significant environmental and economic damage. Effective early prediction mechanisms are critical for minimizing these impacts. In our previous work, we developed a smart and secure wireless sensor network (WSN) utilizing physical sensors to emulate forest fire dynamics and predict fire scenarios using machine learning. Building on this foundation, this study explores the integration of virtual sensors to enhance the prediction capabilities of the WSN. Virtual sensors were generated using polynomial regression models and incorporated into a supervector framework, effectively augmenting the data from physical sensors. The enhanced dataset was used to train a multi-layer perceptron neural network (MLP NN) to classify multiple fire scenarios, covering both early warning and advanced fire states. Our experimental results demonstrate that the addition of virtual sensors significantly improves the accuracy of fire scenario predictions, especially in complex situations like “Fire with Thundering” and “Fire with Thundering and Lightning”. The extended model’s ability to predict early warning scenarios such as lightning and smoke is particularly promising for proactive fire management strategies. This paper highlights the potential of combining physical and virtual sensors in WSNs to achieve superior prediction accuracy and scalability of the field without any extra cost. Such findings pave the way for deploying scalable (cost-effective), intelligent monitoring systems capable of addressing the growing challenges of forest fire prevention and management. We obtained significant results in specific scenarios based on the number of virtual sensors added, while in some scenarios, the results were less promising compared to using only physical sensors. However, the integration of virtual sensors enables coverage of much larger areas, making it a highly promising approach despite these variations. Future work includes further optimization of the virtual sensor generation process and expanding the system’s capability to handle large-scale forest environments. Moreover, utilizing virtual sensors will alleviate many challenges associated with the huge number of deployed physical sensors. Full article

As the main inter-domain routing protocol in today’s internet, the Border Gateway Protocol (BGP) faces serious security risks during actual usage. Research on BGP malicious attack methods requires a realistic network environment, and evaluation methods based on physical networks often suffer from high costs and insufficient flexibility. Thus, we propose an efficient BGP simulated network deployment system based on a virtualization technology called the SOD–BGP. This system, combining cloud computing and virtualization technologies, creates a scalable, highly flexible basic network environment that allows for the automated simulation and evaluation of actual BGP prefix hijacking attack scenarios. A Resource Public Key Infrastructure (RPKI) simulation suite is introduced into the system, emulating a certificate issuance system, certificate storage, and a certificate synchronization verification mechanism, thus aligning the simulation environment with real-world usage scenarios. Finally, we propose a data collection and performance evaluation technique to evaluate BGP networks deploying RPKI under different attack scenarios and to explore the effectiveness of RPKI defense mechanisms at various deployment rates. A comparative analysis with other simulation techniques demonstrates that our approach achieves a balanced performance in terms of deployment speed, complexity, and RPKI integrity, providing a solid simulation technology foundation for large-scale BGP security defense strategies. Full article

The rapid evolution of automotive software necessitates efficient and accurate development and verification processes. This study proposes a virtual electronic control unit (vECU) that allows for precise software testing without the need for hardware, thereby reducing developmental costs and enabling cloud-native development. The software was configured and built on a Hyundai Autoever AUTomotive Open System Architecture (AUTOSAR) classic platform, Mobilgene, and Renode was used for high-fidelity emulations. Custom peripherals in C# were implemented for the FlexTimer, system clock generator, and analog-to-digital converter to ensure the proper functionality of the vECU. Renode’s GNU debugger server function facilitates detailed software debugging in a cloud environment, further accelerating the developmental cycle. Additionally, automated testing was implemented using a vECU tester to enable the verification of the vECU. Performance evaluations demonstrated that the vECU’s execution order and timing of tasks and runnable entities closely matched those of the actual ECU. The vECU tester also enabled fast and accurate verification. These findings confirm the potential of the AUTOSAR-compatible Level-4 vECU to replace hardware in development processes. Future efforts will focus on extending capabilities to emulate a broader range of hardware components and complex system integration scenarios, supporting more diverse research and development efforts. Full article

Increasing power consumption and reliance on non-predictable renewable power generation is pushing the transition from analog to digital power grid substations forward. Grid digitalization helps to reduce substation complexity and therefore costs, and improves observability and management, but introduces new cyber security issues. To make the digital substations secure, cyber security awareness and efficient personnel training is one of the most important research areas as the power grid is a part of critical infrastructure. In our previous work, we have proposed an approach for analyzing cyber security threats and attacks in digital substations based on a case study from Norway. In this article, we present how we developed a tool for emulation of digital substation communication for cyber security awareness based on experiences from the case study. We present technical details of the tool—called the SGSim—so the community can easily replicate the process or only the selected parts. We also freely provide source code on GitHub and distribution in the form of a virtual machine on request. Finally, we validate the tool performance in several scenarios and evaluate its usability on a survey conducted among a wide range of professionals. Full article

Sharing resources through network slicing in a physical infrastructure facilitates service delivery to various sectors and industries. Nevertheless, ensuring security of the slices remains a significant hurdle. In this paper, we investigate the utilization of State-of-the-Art (SoA) Virtual Private Network (VPN) solutions in 5G networks to enhance security and performance when isolating slices. We deploy and orchestrate cloud-native network functions to create multiple scenarios that emulate real-life cellular networks. We evaluate the performance of the WireGuard, IPSec, and OpenVPN solutions while ensuring confidentiality and data protection within 5G network slices. The proposed architecture provides secure communication tunnels and performance isolation. Evaluation results demonstrate that WireGuard provides slice isolation in the control and data planes with higher throughput for enhanced Mobile Broadband (eMBB) and lower latency for Ultra-Reliable Low-Latency Communications (URLLC) slices compared to IPSec and OpenVPN. Our developments show the potential of implementing WireGuard isolation, as a promising solution, for providing secure and efficient network slicing, which fulfills the 5G key performance indicator values. Full article

The measurement of the ground forces on a real structure or mechanism in operation can be time-consuming and expensive, particularly when production cannot be halted to install sensors. In cases in which disassembling the parts of the system to accommodate sensor installation is neither feasible nor desirable, observing the structure or mechanism in operation and quickly deducing its force trends would facilitate monitoring activities in industrial processes. This opportunity is gradually becoming a reality thanks to the coupling of artificial intelligence (AI) with design techniques such as the finite element and multi-body methods. Properly trained inferential models could make it possible to study the dynamic behavior of real systems and mechanisms in operation simply by observing them in real time through a camera, and they could become valuable tools for investigation during the operation of machinery and devices without the use of additional sensors, which are difficult to use and install. In this paper, the idea presented is developed and applied to a simple mechanism for which the reaction forces during operating conditions are to be determined. This paper explores the implementation of an innovative vision-based virtual sensor that, through data-driven training, is able to emulate traditional sensing solutions for the estimation of reaction forces. The virtual sensor and relative inferential model is validated in a scenario as close to the real world as possible, taking into account interfering inputs that add to the measurement uncertainty, as in a real-world measurement scenario. The results indicate that the proposed model has great robustness and accuracy, as evidenced by the low RMSE values in predicting the reaction forces. This demonstrates the model’s effectiveness in reproducing real-world scenarios, highlighting its potential in the real-time estimation of ground reaction forces in industrial settings. The success of this vision-based virtual sensor model opens new avenues for more robust, accurate, and cost-effective solutions for force estimation, addressing the challenges of uncertainty and the limitations of physical sensor deployment. Full article

In a LoRaWAN network, the backend is generally distributed as Software as a Service (SaaS) based on container technology, and recently, a containerized version of the LoRaWAN node stack is also available. Exploiting the disaggregation of LoRaWAN components, this paper focuses on the emulation of complex end-to-end architecture and infrastructures for smart city scenarios, leveraging on lightweight virtualization technology. The fundamental metrics to gain insights and evaluate the scaling complexity of the emulated scenario are defined. Then, the methodology is applied to use cases taken from a real LoRaWAN application in a smart city with hundreds of nodes. As a result, the proposed approach based on containers allows for the following: (i) deployments of functionalities on diverse distributed hosts; (ii) the use of the very same SW running on real nodes; (iii) the simple configuration and management of the emulation process; (iv) affordable costs. Both premise and cloud servers are considered as emulation platforms to evaluate the resource request and emulation cost of the proposed approach. For instance, emulating one hour of an entire LoRaWAN network with hundreds of nodes requires very affordable hardware that, if realized with a cloud-based computing platform, may cost less than USD 1. Full article

The rapid evolution of 5G technology, while offering substantial benefits, concurrently presents complex cybersecurity challenges. Current cybersecurity systems often fall short in addressing challenges such as the lack of realism of the 5G network, the limited scope of attack scenarios, the absence of countermeasures, the lack of reproducible, and open-sourced cybersecurity training environments. Addressing these challenges necessitates innovative cybersecurity training systems, referred to as “cyber ranges”. In response to filling these gaps, we propose the Cyber5Gym, an integrated cyber range that enhances the automation of virtualized cybersecurity training in 5G networks with cloud-based deployment. Our framework leverages open-source tools (i) Open5GS and UERANSIM for realistic emulation of 5G networks, (ii) Docker for efficient virtualization of the training infrastructure, (iii) 5Greply for emulating attack scenarios, and (iv) Shell scripts for automating complex training operations. This integration facilitates a dynamic learning environment where cybersecurity professionals can engage in real-time attack and countermeasure exercises, thus significantly improving their readiness against 5G-specific cyber threats. We evaluated it by deploying our framework on Naver Cloud with 20 trainees, each accessing an emulated 5G network and managing 100 user equipments (UEs), emulating three distinct attack scenarios (SMC-Reply, DoS, and DDoS attacks), and exercising countermeasures, to demonstrate the cybersecurity training. We assessed the effectiveness of our framework through specific metrics such as successfully establishing the 5G network for all trainees, accurate execution of attack scenarios, and their countermeasure implementation via centralized control of the master using automated shell scripts. The open-source foundation of our framework ensures replicability and adaptability, addressing a critical gap in current cybersecurity training methodologies and contributing significantly to the resilience and security of 5G infrastructures. Full article

In the transition from virtual environments to real-world applications, the role of physics engines is crucial for accurately emulating and representing systems. To address the prevalent issue of inaccurate simulations, this paper introduces a novel physics engine uniquely designed with a compliant contact model designed for robotic grinding. It features continuous and variable time-step simulations, emphasizing accurate contact force calculations during object collision. Firstly, the engine derives dynamic equations considering spring stiffness, damping coefficients, coefficients of restitution, and external forces. This facilitates the effective determination of dynamic parameters such as contact force, acceleration, velocity, and position throughout penetration processes continuously. Secondly, the approach utilizes effective inertia in developing the contact model, which is designed for multi-jointed robots through pose transformation. The proposed physics engine effectively captures energy conversion in scenarios with convex contact surface shapes through the application of spring dampers during collisions. Finally, the reliability of the contact solver in the simulation was verified through bouncing ball experiments and robotic grinding experiments under different coefficients of restitution. These experiments effectively recorded the continuous variations in parameters, such as contact force, verifying the integral stability of the system. In summary, this article advances physics engine technology beyond current geometrically constrained contact solutions, enhancing the accuracy of simulations and modeling in virtual environments. This is particularly significant in scenarios wherein there are constant changes in the outside world, such as robotic grinding tasks. Full article

Researchers are exploring methods that exploit digital twins as all-purpose abstractions for sophisticated modelling and simulation, bringing elements of the real world into the virtual realm. Digital twins are essential elements of the digital transformation of society, which mostly benefit manufacturing, smart cities, healthcare contexts, and in general systems that include humans in the loop. As the metaverse concept continues to evolve, the line separating the virtual and the real will progressively fade away. Considering the metaverse’s goal to emulate our social reality, it becomes essential to examine the aspects that characterise real-world interaction practices and explicitly model both physical and social contexts. While the unfolding metaverse may reshape these practices in distinct ways from their real-world counterparts, our position is that it is essential to incorporate social theories into the modelling processes of digital twins within the metaverse. In this work, we discuss our perspective by introducing a digital practice model inspired by the theory of social practice. We illustrate this model by exploiting the scenario of a virtual grocery shop designed to help older adults reduce their social isolation. Full article

The defence-in-depth (DiD) methodology is a defensive approach usually performed by network administrators to implement secure networks by layering and segmenting them. Typically, segmentation is implemented in the second layer using the standard virtual local area networks (VLANs) or private virtual local area networks (PVLANs). Although defence in depth is usually manageable in small networks, it is not easily scalable to larger environments. Software-defined networks (SDNs) are emerging technologies that can be very helpful when performing network segmentation in such environments. In this work, a corporate networking scenario using PVLANs is emulated in order to carry out a comparative performance analysis on defensive strategies regarding CPU and memory usage, communications delay, packet loss, and power consumption. To do so, a well-known PVLAN attack is executed using simulated attackers located within the corporate network. Then, two mitigation strategies are analysed and compared using the traditional approach involving access control lists (ACLs) and SDNs. The results show the operation of the two mitigation strategies under different network scenarios and demonstrate the better performance of the SDN approach in oversubscribed network designs. Full article