Mission-critical Systems Research Articles

Active mission assignment for improving the effectiveness of opportunistic maintenance in a fleet of mission-critical systems

In a fleet of mission-critical systems, maintaining high availability for each individual system is vital to ensure consistent fleet readiness to meet mission demands. This study introduces a novel mission assignment strategy aimed at actively aligning maintenance schedules within each system to maximise opportunistic maintenance potential, thus enhancing system availability. However, solely focusing on system-level assignments may result in simultaneous maintenance needs across the fleet, leading to resource conflicts. The proposed strategy addresses this issue by coordinating mission assignments to consider both the alignment of schedules within a system and the even distribution of schedules among systems to prevent fleet-level conflicts. Two operational conditions, intra-system and inter-system balance, are defined to evaluate the criticality of each system at both system and fleet levels. Based on these conditions, scheduling rules are developed to determine assignment priority across the fleet in a two-phase process. Simulation studies demonstrate the effectiveness of this approach, showing a 2% improvement in system availability, equivalent to a two-month reduction in downtime across the fleet over a one-year period. The results underscore the advantages of the proposed strategy in optimising maintenance operations in complex fleet environments with diverse mission requirements.

Optimising resource-constrained fleet selective maintenance with asynchronous maintenance breaks

This paper offers a novel and significant extension of the Fleet Selective Maintenance Problem (FSMP) by considering asynchronous maintenance breaks and resource-constrained maintenance planning. This constitutes a significant shift from the conventional focus on synchronous breaks for the FSMP formulated to plan maintenance for fleets of mission-critical systems. This paper establishes a theoretical link between the Selective Maintenance Problem (SMP) and the Resource Constrained Project Scheduling Problem (RCPSP). The proposed FSMP formulation for asynchronous breaks is more general and versatile in adapting to a broad spectrum of operational constraints and resource scarcities. Numerical experiments are conducted that highlights the trade-offs between the timing and quality levels of maintenance activities and the consumption of resources that maintenance planners can make to obtain the best system performance for the budget and maintenance windows available.

Unsourced Multiple Access for Mission-Critical Control Systems in Industrial Internet of Things

Unsourced Multiple Access for Mission-Critical Control Systems in Industrial Internet of Things

МОДЕЛИРОВАНИЕ НАРУШИТЕЛЯ, ИНФРАСТРУКТУРЫ И АТАК В СИСТЕМАХ ИНФОРМАЦИОННОЙ БЕЗОПАСНОСТИ

Formal models of subjects, infrastructure and attacks for information security systems are proposed. The models include descriptions of information security operators, administrators, users and violators, taking into account their knowledge, qualifications and initial conditions. A comprehensive intruder model is presented, including initial knowledge and access rights, initial location, qualifications and goals. Infrastructure models, vulnerabilities, and information collection methods are also considered, which makes it possible to more accurately predict the behavior of violators and develop effective protection strategies. The results of the study show that the proposed models significantly improve the accuracy of risk assessment and security planning, which is especially important for mission-critical information systems. The practical significance lies in the possibility of using models to develop and improve information network security systems. The results of the practical implementation of the model on real data are also presented.

Noise ordinances: The key to Environmental, Social and Governance (ESG) issues surrounding datacenters

The declaration of Noise Control Act of 1972 was a historic moment, whereby the Environmental Protection Agency (EPA) of the United States appropriately recognized and acted toward protecting the American population's health and welfare from the dangers of noise emission. And while this policy served as the Gold Standard for the creation of noise policies around the world, the decision to transfer the responsibility of regulating noise to state and local levels of government is one that has had a negative impact on the acoustical industry in the United States. This paper outlines instances where defined noise ordinances would have had protected vulnerable populations (in contiguous areas), as well as the parties affiliated with datacenters. The document also outlines methodological policies, guidance for adoption or updating of noise ordinances for Authorities Having Jurisdiction (AHJ), examples of mission-critical systems contributing to noise emission and the most effective solutions available to achieve compliance.

MTD-Diorama: Moving Target Defense Visualization Engine for Systematic Cybersecurity Strategy Orchestration.

With the advancement in information and communication technology, modern society has relied on various computing systems in areas closely related to human life. However, cyberattacks are also becoming more diverse and intelligent, with personal information and human lives being threatened. The moving target defense (MTD) strategy was designed to protect mission-critical systems from cyberattacks. The MTD strategy shifted the paradigm from passive to active system defense. However, there is a lack of indicators that can be used as a reference when deriving general system components, making it difficult to configure a systematic MTD strategy. Additionally, even when selecting system components, a method to confirm whether the systematic components are selected to respond to actual cyberattacks is needed. Therefore, in this study, we surveyed and analyzed existing cyberattack information and MTD strategy research results to configure a component dataset. Next, we found the correlation between the cyberattack information and MTD strategy component datasets and used this to design and implement the MTD-Diorama data visualization engine to configure a systematic MTD strategy. Through this, researchers can conveniently identify the attack surface contained in cyberattack information and the MTD strategies that can respond to each attack surface. Furthermore, it will allow researchers to configure more systematic MTD strategies that can be used universally without being limited to specific computing systems.

Securing Your Eggs in Multiple Baskets — Assuring a Resilient and Secure Supply Chain

AbstractThe global supply chain is a complex system of systems made up of and relying on other complex systems of systems (SoS) to achieve its goals. To take a typical example, Enterprise A is supplied essential parts on a regular basis to manufacture its products. To place the order requires global financial systems, integrated email systems, the internet, multiple telecommunications systems, and supply software provided by large companies. To deliver the parts may require air and maritime transportation systems, the rail network, interstate highway systems, road haulage companies, state and local transportation systems and so forth. When any of these complex systems fail, the impact can be global, and the results catastrophic. Recent examples include the shortage of Personal Protective Equipment (PPE) during the COVID pandemic, computer chip shortages delaying the assembly and sales of cars, and, most recently, the baby formula shortage. These were due to disruptions in the supply chain caused by an overreliance on single sourced suppliers who failed to deliver, transportation disruptions, outsourcing of critical parts, supplies, medicines to distant countries, and/or an overreliance on “Just In Time” for inventory management. This is the case of placing too many eggs in too few baskets, and often just one basket. Counterfeit or substandard parts and products can enter the supply chain via graft, breaks in chain of custody, or carelessness. This has included critical mechanical parts on aircraft, chips containing spyware, and substandard or out of date medicines substituted for the real thing resulting in serious illness and death. This complex SoS needs to be examined, studied, and understood in the same way as a mission critical system; threats, vulnerabilities, and risks need to be identified and mitigated and assurance cases defined to ensure a solid and reliable supply chain. This paper will look at the supply chain of an example factory system to determine how some of these problems can be predicted, prevented, mitigated, and solved using the UAF, RAAML and assurance case techniques.

From Functional Arrangement to Vulnerability Assessment: Automating Naval Ship Design for Enhanced Survivability Analysis

A novel method has been developed to rapidly assess vulnerability of a new platform which has been generated through a packing approach. This method quickly transforms a volumetric packing model into a surface model that includes ship structure including doors and hatches, mission critical systems and the crew. A weapon model was developed taking into account the unpredictability of a threat by generating multiple scenarios with the Monte Carlo method. Based on this set of simulations vulnerability measures can be introduced in a weight efficient manner. This in turn will allow the naval architects to design safer naval ships in balance with other requirements. This paper describes the process of vulnerability analysis in early ship designs and the feedback loop of conclusions to the designers.

Vision for Emergency Management: Conceptualizing Mission-Critical Ecosystems

Emergency management is seldom viewed through the lens of enterprises/industries, which aim to safeguard their critical missions to deliver seamless services. This article advocates for an integrative perspective on mission-critical (eco)systems. In the digital transformation landscape, the traditional notions of "mission-critical systems," often associated with physical spaces like control facilities or hardware-software crucial for business operations, are challenged. Based on document reviews, this article argues for a holistic comprehension of an organization's mission-critical ecosystems, considering internal and external factors across physical, digital, and human aspects. The article uses renewable energy and e-health as cases. The overarching goal is to expand the research scope in emergency management by examining current concerns and current trends in emergency management domain, combining preparedness, resilience, and cybersecurity. This comprehensive approach aims to enhance our ability to navigate and respond effectively to emergencies in an increasingly complex and interconnected world.

CyberGrid: an IEC61850 protocol-based substation automation virtual cyber range for cybersecurity research in the smart grid

ABSTRACT A cyber range provides a controlled environment for simulating mission-critical systems for cybersecurity research following the high risks involved in conducting experiments in real-life systems. Existing cyber ranges do not provide close emulation of Cyber-Physical Systems (CPS) in the Smart Grid Networks (SGNs), with emphasis on industry-based proprietary and IED protocols. This paper presents CyberGrid Testbed – a virtual Cyber-Range developed by the CyberSCADA Research Laboratory at Obafemi Awolowo University, Ile-Ife, Nigeria, which emulates Substation Automation processes with IEC61850 and Modbus/TCP protocols and support for MMS, and IED. This was built on OpenPLC6185, simulating Twelve attack patterns, and four attack types.

VR-based digital twin for remote monitoring of mining equipment: Architecture and a case study

BackgroundTraditional methods for monitoring mining equipment rely primarily on visual inspections, which are time-consuming, inefficient, and hazardous. This article introduces a novel approach to monitoring mission-critical systems and services in the mining industry by integrating virtual reality (VR) and digital twin (DT) technologies. VR-based DTs enable remote equipment monitoring, advanced analysis of machine health, enhanced visualization, and improved decision making. MethodsThis article presents an architecture for VR-based DT development, including the developmental stages, activities, and stakeholders involved. A case study on the condition monitoring of a conveyor belt using real-time synthetic vibration sensor data was conducted using the proposed methodology. The study demonstrated the application of the methodology in remote monitoring and identified the need for further development for implementation in active mining operations. The article also discusses interdisciplinarity, choice of tools, computational resources, time and cost, human involvement, user acceptance, frequency of inspection, multiuser environment, potential risks, and applications beyond the mining industry. ResultsThe findings of this study provide a foundation for future research in the domain of VR-based DTs for remote equipment monitoring and a novel application area for VR in mining.

Leveraging Variable Density Honeycomb Structures for Innovative Design in Mission-Critical Embedded Devices

The imperative for lightweighting technologies, paramount in mission-critical cyber-physical systems (CPSs) including aerospace, automotive and allied sectors, hinges upon optimizing energy efficiency and curbing product weight. Honeycomb structures, celebrated for their exceptional strength-to-weight ratio, have indisputably guided the pursuit of lightweight design. This paper expounds upon the versatility of honeycomb structures by scrutinizing their in-plane mechanical attributes. Leveraging finite element simulations and polynomial fitting, we enhance the prevailing equivalent elastic modulus model for uniform honeycomb structures, expanding its domain to encompass a broader spectrum of relative density values. Deliberations ensue concerning the model’s constraints and its inapplicability to nonuniform honeycomb structures. The investigation introduces nodes as pivotal influencers in the mechanical comportment of nonuniform honeycomb structures, delineating the nexus between the equivalent elastic modulus and node dimensions through a fusion of finite element simulations and mechanical experimentation. Furthermore, this research delves into the tenets and constructs of density-based variable density methodologies within the ambit of topology optimization, with an overarching goal of maximizing stiffness. We furnish a holistic design protocol for optimizing honeycomb structures, underscored by a pragmatic instantiation of the density-based variable density approach. Scrutinizing the geometric interplay between honeycomb structures and design spaces, we posit an innovative paradigm employing concentric circles to approximate cellular envelopes, streamlining numerical cartography and the conversion of optimization outputs into variable density honeycomb configurations. Evaluation of the in-plane mechanical attributes of variable density honeycomb structures reveals that TPU material augments the resilience of both uniform and variable density honeycomb structures, whereas topology optimization amplifies specific stiffness and resilience modulus in variable density honeycomb structures relative to their uniform counterparts. This study sheds light on the complexities of honeycomb structures, providing valuable insights for their optimization in lightweight applications.

Reliability non-functional requirement evaluation in mission-critical systems with an architectural strategy for future systems

Most of the modern defensive systems have trusted the software to meet the functional requirements of the system. Software architecture has been a key parameter of determinant software quality. Therefore, the software architecture is a critical process for software quality. According to the US Department of Defense (DoD), the ability to evaluate software architecture has a favorable efficacy on the current development system. In the architectural design process, several decisions have been made that have some effect on the system level. One of these important decisions is choosing the appropriate and optimal architectural style. Considering the vital role of reliability in security-sensitive software systems, one of the main criteria in choosing the style of software architecture is high reliability. It has been obvious that, in each system, a special combination of quality attributes has been considered and the lack of quantitative analysis of the effect of software architecture styles on quality attributes has prevented the effective utilization of architectural styles. This research explains the concept of the software architecture principle and also evaluates the reliability and its software architecture in the field of fast and autonomous intercity trains of Berlin S-Bahn intercity in Germany as a case study. The results described that object-oriented styles, repositories and implicit invocation should be considered for the architectural style of this system.

Approach based on STPA extended with STRIDE and LINDDUN, and blockchain to develop a mission-critical e-voting system

Voting is essential to assure democracy. The voting process is supported by mission-critical systems that have among others functional, cybersecurity, and data privacy requirements. Comprehensive approaches are required to identify the requirements and technologies needed to design the solution. STPA is a method for identifying system safety requirements that have been extended to identify cybersecurity requirements. LINDDUN is a privacy threat modeling methodology that supports analysts in privacy-eliciting and mitigating threats in software architectures. Blockchain is a technology that uses a peer-to-peer computer network as a public distributed ledger. We propose an approach that uses STPA and its extensions to identify the cybersecurity and data privacy requirements, and incorporates the blockchain technology to design the solution for the mission-critical e-voting system. We built a proof of concept of the solution and performed cybersecurity and data privacy tests. The tests showed that the solution meets the critical cybersecurity and data privacy requirements. The major contributions of this paper include an approach that employs cybersecurity and data privacy threat modeling techniques to enhance the STPA analysis of a system, and the design of a Blockchain-based, verifiable e-voting system.

Residual Physics and Post-Posed Shielding for Safe Deep Reinforcement Learning Method.

Deep reinforcement learning (DRL) has been researched for computer room air conditioning unit control problems in data centers (DCs). However, two main issues limit the deployment of DRL in actual systems. First, a large amount of data is needed. Next, as a mission-critical system, safe control needs to be guaranteed, and temperatures in DCs should be kept within a certain operating range. To mitigate these issues, this article proposes a novel control method RP-SDRL. First, Residual Physics, built using the first law of thermodynamics, is integrated with the DRL algorithm and a Prediction Model. Subsequently, a Correction Model adapted from gradient descent is combined with the Prediction Model as Post-Posed Shielding to enforce safe actions. The RP-SDRL method was validated using simulation. Noise is added to the states of the model to further test its performance under state uncertainty. Experimental results show that the combination of Residual Physics and DRL can significantly improve the initial policy, sample efficiency, and robustness. Residual Physics can also improve the sample efficiency and the accuracy of the prediction model. While DRL alone cannot avoid constraint violations, RP-SDRL can detect unsafe actions and significantly reduce violations. Compared to the baseline controller, about 13% of electricity usage can be saved.

Practical Byzantine Fault Tolerance-Enhanced Blockchain-Enabled Data Sharing System: Latency and Age of Data Package Analysis

Data timeliness, privacy, and security are key enablers for data-sharing systems to support time-sensitive and mission-critical systems and applications. While blockchain-enabled data sharing frameworks can offer reliable security and privacy when properly implemented, the timeliness of data and the related latency are important issues that can limit the adoption of blockchain in large-scale mission-critical applications. This paper thus carried out a performance analysis of the blockchain-enabled data-sharing framework from latency and data age perspectives to investigate the suitability of blockchain technology in data sharing systems. To achieve this, the uniqueness of such systems such as transactions validation latency, transaction generation rate, waiting time, blockchain-appending rate, and overall communication latency were jointly studied. The communication latency was characterized following the spatiotemporal modeling approach. We further adopted the practical Byzantine fault tolerance (PBFT) consensus protocol due to its well discussed suitability in large-scale data sharing applications and captured the validation stages of such a PBFT scheme using the Erlang distribution of order <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$k$</tex-math></inline-formula> . Simulations results show that various influential system parameters must be carefully considered when adopting blockchain technology in time-sensitive data sharing applications. This will guide the adoption of blockchain technology in various data sharing applications and systems.

Design and Control for High-Reliability Power Electronics: State-of-the-Art and Future Trends

Electrification is a mega-trend in the modern economy, urged by the need for a more ecological and sustainable impact of new technologies, among many other merits related to the process of electrification. The widespread adoption of renewable energy, transportation electrification, energy storage systems and smart manufacturing is remarkable. As a result, power electronics has become the critical enabling technology for improving energy efficiency and sustainability. In recent years, the reliability of power electronic equipment has been under scrutiny, especially in mission-critical applications of power electronics converters. Recently, special attention has been paid to the development of lifetime models of the main electronic components, which could then be applied to probabilistic analysis based on the mission profile of system-level reliability. This prediction methodology has some limitations because it does not consider external factors and agents other than the wear itself. Redundancy has been the typical approach to improve the availability of mission critical power electronic systems, which could be associated with considerable extra cost. Fault-tolerant converters were proposed as a more cost-effective alternative solution that could also extend the service life. The maintenance cost could be reduced by using active thermal control, which allows the balancing of wear damage in modular power electronic converters and, consequently, the scheduling of maintenance events. A further step could be taken with the application of real-time condition monitoring of systems, which has evolved into the concepts of predictive and prescriptive maintenance that allows for prediction and mitigation of faults. These techniques are under active development and are expected to benefit from new methods and technologies from rapidly progressing areas of artificial intelligence and digital twin. This paper provides a detailed overview on the recent trends and advances in the field of high-reliability power electronics systems.

A flexible soft error mitigation framework leveraging dynamic partial reconfiguration technology

Fault tolerance is crucial for mission-critical FPGA-based systems in radiation environments. Soft-core processors in these systems, performing both control and computational tasks, require efficient soft error mitigation techniques to enhance their fault tolerance. In this paper, we investigate the variation trends in the fault tolerance of various processor components as the software workload changes. Based on our investigation, we propose a reconfigurable soft error mitigation framework that dynamically switches the hardening strategies for the processor according to the running workloads. The innovative application of dynamic partial reconfiguration technique in FPGAs enables time-multiplexing of the same circuit region to accommodate various hardening schemes, consequently achieving high area efficiency. We apply the framework to an open-source dual-issue superscalar RISC-V processor on a Xilinx ZCU102 FPGA board. Compared to traditional spatial redundancy-based hardening techniques, the proposed framework achieves a 20.84 % reduction in LUT utilization and a 20.53 % reduction in flip-flop utilization. The effectiveness of our framework has been evaluated through fault injection campaigns. The results indicate that, on average, only 0.05 % of faults would lead to system failure after hardening. Therefore, our work offers a new perspective on dynamic soft error mitigation in reconfigurable systems.

Maximizing Efficiency in Energy Trading Operations through IoT-Integrated Digital Twins.

The Internet of Things (IoT) has brought about significant transformations in multiple sectors, including healthcare and navigation systems, by offering essential functionalities crucial for their operations. Nevertheless, there is ongoing debate surrounding the unexplored possibilities of the IoT within the energy industry. The requirement to better the performance of distributed energy systems necessitates transitioning from traditional mission-critical electric smart grid systems to digital twin-based IoT frameworks. Energy storage systems (ESSs) used within nano-grids have the potential to enhance energy utilization, fortify resilience, and promote sustainable practices by effectively storing surplus energy. The present study introduces a conceptual framework consisting of two fundamental modules: (1) Power optimization of energy storage systems (ESSs) in peer-to-peer (P2P) energy trading. (2) Task orchestration in IoT-enabled environments using digital twin technology. The optimization of energy storage systems (ESSs) aims to effectively manage surplus ESS energy by employing particle swarm optimization (PSO) techniques. This approach is designed to fulfill the energy needs of the ESS itself as well as meet the specific requirements of participating nano-grids. The primary objective of the IoT task orchestration system, which is based on the concept of digital twins, is to enhance the process of peer-to-peer nano-grid energy trading. This is achieved by integrating virtual control mechanisms through orchestration technology combining task generation, device virtualization, task mapping, task scheduling, and task allocation and deployment. The nano-grid energy trading system's architecture utilizes IoT sensors and Raspberry Pi-based edge technology to enable virtual operation. The evaluation of the proposed study is carried out through the examination of a simulated dataset derived from nano-grid dwellings. This research analyzes the efficacy of optimization approaches in mitigating energy trading costs and optimizing power utilization in energy storage systems (ESSs). The coordination of IoT devices is crucial in improving the system's overall efficiency.

Evolvable Hardware Based Optimal Position Control of Quadcopter

Trading off performance metrics in control design for position tracking is unavoidable. This has severe consequences in mission-critical systems such as quadcopter applications. The controller area and propulsion energy are conflicting design parameters, whereas the reliability and tracking speed are related metrics to be optimized. In this research, a switching-based position controller was co-simulated with the quadcopter model. Performance analysis of the Field Programmable Gate Array (FPGA)-based controller validates a better scheme for tracking speed, propulsion energy, and reliability optimization under similar error performance. To improve the computation power and controller area, the dynamic partial reconfiguration(DPR) approach has been adapted and implemented on FPGA using the Vivado Integrated Development Environment (IDE), where a ranking-based approach brings into action either proportional derivative, sliding mode, or model predictive controllers for each dimension of position tracking. It is verified by analyzing the cumulative tracking speed, reliability, controller area, and propulsion energy metrics that the proposed controller can optimize all these metrics within three successive iterations of tracking either in the same direction or in any combination of directions. Concerning the implementation results of the controller with the switching-based controller, there is 6 % computation power and 30 % resource savings due to DPR .