Cyber-physical Systems Applications Research Articles

Network lifetime improvement using landmark-assisted mobile sink scheduling for cyber-physical system applications

Improving the lifetime of a wireless sensor network is a challenging issue in the development of energy-efficient cyber-physical systems, especially in the design of sensor data aggregation protocols. Mobile sinks are typically used in this context to increase the lifetime of the sensor network in a cyber-physical system. In this work, a landmark-assisted mobile sink scheduling scheme is proposed for designing an energy-efficient data aggregation protocol. A landmark-node identification method along with network clustering is first developed using random walks over network graphs. Subsequently, using the locations of landmark-nodes, a mobile sink scheduling method is developed for sensor data aggregation in an extended Kalman filtering framework. This method is robust since location information of the landmark-nodes is also continuously updated in the Kalman filtering framework. Experiments on identifying landmark-nodes and mobile sink scheduling are conducted on the Intel Berkeley Research Lab dataset and over a real WSN test bed with a Kobuki–Yujin robot. Experimental results obtained for network lifetime analysis and energy-efficiency for various network configurations indicate an improvement over standard methods and are motivating enough for use in practical cyber-physical system applications.

Energy-Efficient Data Collection Over AUV-Assisted Underwater Acoustic Sensor Network

Most applications of underwater cyber-physical system (UCPS) demand reliable data collection in an efficient and timely manner. However, the energy-constrained characteristic on acoustic communication makes it challenging to collect data. In this paper, we study the energy-efficient data collection for UCPS over autonomous underwater vehicle (AUV) assisted underwater acoustic sensor network. The sensor nodes perceive local physical parameters, whose lifetime is strictly restricted by local power. The AUV that has relatively sufficient energy is adopted to retrieve data from sensor nodes. To balance energy consumption and prolong underwater network lifetime, the energy optimization problem is formulated as minimizing the sum of edge lengths of a particular graph. Then, a min-weighted rigid graph based topology optimization scheme is developed for sensor deployment. With the optimized network topology, a local routing decision algorithm is developed for each sensor node to relay the collected data to the data collectors (sinks). A dynamic value-based path planning strategy is also designed for the AUV to dynamically visit data collectors to maximize the value of information (VoI) within a given time. Finally, simulation results demonstrate that the network lifetime with the topology optimization scheme can be prolonged, and the dynamic value-based path planning strategy can improve the VoI on AUV.

The Safety Analysis: Disagreement of Wireless Communication-Based Consensus

This letter considers the recent and practically relevant problem of safety in cyber-physical systems (CPS). Practical applications of CPS can be designed through the use of wireless multi-agent systems (MAS) since they provide flexibility and interoperability of the system functions. On the other hand, the performance of wireless MAS is prone to jamming attacks and the destructive effects of wireless channels. The aim of this letter is to determine safety bounds on wireless CPS under jamming attacks in the presence of additive white Gaussian noise (AWGN) and wireless fading channels. The impact of both wireless channel impairments and jamming attacks on the performance of wireless MAS has been investigated for the first time. The disagreement vector, defined as the deviation from the desired consensus value of MAS based on the quantization error, is analyzed and investigated for AWGN and fading channels. Theoretical results are supported by matching simulation results.

An Attack-Resilient CPS Architecture for Hierarchical Control: A Case Study on Train Control Systems

This article presents an attack-resilient architecture for cyber-physical systems (CPSs). As a case study, the authors build a radio-based train control testbed and validate the proposed resilient design architecture. The target CPS application is a hierarchical control system.

Real-Time Data Retrieval With Multiple Availability Intervals in CPS Under Freshness Constraints

Maintaining the temporal validity of real-time data in cyber-physical systems (CPSs) is of critical importance to ensure correct decision making and appropriate system operation. Most existing work on real-time data retrieval assumes that the real-time data under study are always available, and the developed scheduling algorithms mainly focus on making real-time decisions while meeting the temporal validity (freshness) constraints. This assumption, however does not hold in many real-life CPS applications with intermittent data availability, such as in energy harvesting-based sensing systems. In this paper, we study the multi-interval availability-constrained fresh data retrieval (MAFDR) problem, which aims to retrieve all required real-time data on time for a set of decision tasks while taking both the temporal validity and data availability constraints into consideration. We present the formulation of the MAFDR problem and study its complexity under different settings. For the scenario of single decision task with unit-size data retrieval time, we propose a polynomial-time optimal data retrieval algorithm, which comprises a task finish time selection phase and an optimal retrieval schedule construction phase. For the general scenario of multiple decision tasks with nonunit-size data retrieval time, we provide an integer linear programming formulation for the MAFDR problem and propose a fast heuristic algorithm based on max flow. The effectiveness of the proposed algorithms has been validated through extensive experiments by comparing to the optimal solution and the state-of-the-art approach.

Developing Self-Similar Hybrid Control Architecture Based on SGAM-Based Methodology for Distributed Microgrids

Cyber-Physical Systems (CPS) are the complex systems that control and coordinate physical infrastructures, which may be geographically apart, via the use of Information and Communication Technology (ICT). One such application of CPS is smart microgrids. Microgrids comprise both power consuming and power producing infrastructure and are capable of operating in grid connected and disconnected modes. Due to the presence of heterogeneous smart devices communicating over multiple communication protocols in a distributed environment, a system architecture is required. The objective of this paper is to approach the microgrid architecture from the software and systems’ design perspective. The architecture should be flexible to support various multiple communication protocols and is able to integrate various hardware technologies. It should also be modular and scalable to support various functionalities such as island mode operations, energy efficient operations, energy trading, predictive maintenance, etc. These requirements are the basis for designing the software architecture for the smart microgrids that should be able to manage not only electrical but all energy related systems. In this work, we propose a distributed, hybrid control architecture suited for microgrid environments, where entities are geographically distant and need to operate in a cohesive manner. The proposed system architecture supports various design philosophies such as component-based design, hierarchical composition of components, peer-to-peer design, distributed decision-making and controlling as well as plug-and-play during runtime. A unique capability of the proposed system architecture is the self-similarity of the components for the distributed microgrids. The benefit of the approach is that it supports these design philosophies at all the levels in the hierarchy in contrast to a typical centralized architectures where decisions are taken only at the global level. The proposed architecture is applied to a real system of 13 residential buildings in a low-voltage distribution network. The required implementation and deployment details for monitoring and controlling 13 residential buildings are also discussed in this work.

Identifying Promising Application Areas for Cyber-Physical and Complex Event Processing in Logistics Practice

In the course of the ongoing era of digitization, cyber-physical systems and complex event processing belong to the most discussed technologies nowadays. The huge challenge that digitization is forming to the transportation and logistics sector is largely accepted by the responsible organizations. Despite initial steps being taken towards digitized value-creation, many professionals wonder about how to realize the ideas and stumble with the precise steps to be taken. With the vision of smart logistics in mind and cost-efficient technologies available, they require a systematic methodology to exploit the potentials accompanying digitization. With the help of an effective and targeted workshop procedure, potentially appropriate application areas with promising benefit potentials can be identified effectively. Such a workshop procedure needs to be a stepwise approach in order to carefully consider all the relevant aspects and to allow for organizational acceptance to grow. In three real-world use case examples from different areas of the transportation and logistics industry, promising applications of cyber-physical systems and complex event processing are identified and pertaining event patterns of critical situations developed in order to make realization easier at a later stage. Each use case example exhibits a frequently occurring problem that can be effectively addressed by using the above-mentioned technology.

Classification of cyber-physical production systems applications: Proposition of an analysis framework

Cyber-physical systems have encountered a huge success in the past decade in several scientific communities, and specifically in production topics. The main attraction of the concept relies in the fact that it encompasses many scientific topics that were distinct before. The downside is the lack of readability of the current developments about cyber-physical production systems (CPPS). Indeed, the large scientific area of CPPS makes it difficult to identify clearly and rapidly, in the various applications that were made of CPPS, what are the choices, best practices and methodology that are suggested and that could be used for a new application. This work intends to introduce an analysis framework able to classify those developments. An extensive study of literature enabled to extract the major criteria that are to be used in the framework, namely: Development Extent; Research Axis; Instrumenting; Communication standards; Intelligence deposit; Cognition level; Human factor. Several recent examples of CPPS developments in literature are used to illustrate the use of the framework and brief conclusions are drawn from the comparative analysis of those examples.

Dependable Deep Computation Model for Feature Learning on Big Data in Cyber-Physical Systems

With the ongoing development of sensor devices and network techniques, big data are being generated from the cyber-physical systems. Because of sensor equipment occasional failure and network transmission unreliability, a large number of low-quality data, such as noisy data and incomplete data, is collected from the cyber-physical systems. Low-quality data pose a remarkable challenge on deep learning models for big data feature learning. As a novel deep learning model, the deep computation model achieves superior performance for big data feature learning. However, it is difficult for the deep computation model to learn dependable features for low-quality data, since it uses the nonlinear function as the encoder. In this article, a dependable deep computation model is proposed for feature learning on low-quality big data in cyber-physical systems. Specially, a regularity is added into the objective function of the deep computation model to obtain reliable features in the intermediate-level representation space. Furthermore, a learning algorithm based on the back-propagation strategy is devised to train the parameters of the proposed model. Finally, experiments are conducted on three representative datasets and a real dataset to evaluate the effectiveness of the dependable deep computation model for low-quality big data feature learning. Results show that the proposed model achieves a remarkable result for the tasks of classification, restoration, and prediction, proving the potential of this work for practical applications in cyber-physical systems.

Improve the Localization Dependability for Cyber-Physical Applications

Localization for mobile group users is one of the important applications in cyber-physical systems. However, due to the sparse deployment of anchors and the instability of signals in the wireless environment, users cannot receive information from adequate anchors, which leads to the localization quality being undependable and unacceptable. To solve this problem, we propose exploiting the localized users as the mobile anchors for localizing the nonlocalized users. These mobile users cooperate as a whole group to improve the localization accuracy. Moreover, to decrease the communication cost among users, an algorithm for electing mobile anchors is designed, with several provable properties. This electing algorithm is a distributed method, without advanced negotiations among mobile users. In addition, for the scenarios with a crowd of users, we divide the users into different groups according to their distance information, which can ensure that only the dependable anchors are used for the localization. Extensive experimental results demonstrate that the localization dependability can be improved obviously. In terms of localization probability, our method outperforms the traditional fixed anchors-based method by approximately 70% with a small increment of communication cost (about 30%), and outperforms the method in which all the localized users are exploited as mobile anchors by about 50% with about a 70% decrement of communication cost.

Model and Tool Integration Platforms for Cyber–Physical System Design

Design methods and tools evolved to support the principle of separation of concerns in order to manage engineering complexity. Accordingly, most engineering tool suites are vertically integrated but have limited support for integration across disciplinary boundaries. Cyber–physical systems (CPSs) challenge these established boundaries between disciplines, and thus, the status quo on the tools market. The question is how to create the foundations and technologies for semantically precise model and tool integration that enable reuse of existing commercial and open source tools in domain-specific design flows. In this paper, we describe the lessons learned in the design and implementation of an experimental design automation tool suite, OpenMETA, for complex CPS in the vehicle domain. The conceptual foundation for the integration approach is platform-based design: OpenMETA is architected by introducing two key platforms: the model integration platform and the tool integration platform. The model integration platform includes methods and tools for the precise representation of semantic interfaces among modeling domains. The key new components of the model integration platform are model integration languages and the mathematical framework and tool for the compositional specification of their semantics. The tool integration platform is designed for executing highly automated design-space exploration. Key components of the platform are tools for constructing design spaces and model composers for analytics workflows. The paper concludes with describing experience and lessons learned by using OpenMETA in drivetrain design and by adapting OpenMETA to substantially different CPS application domains.

The application of CPS in library management: a survey

PurposeThe purpose of this paper is to present the current state research of cyber-physical system (CPS) and its application in libraries. CPS is a kind of large-scale and networked system that consists of physical and cyber elements and is currently of interest in academia, industry and government. In this survey, the definitions, theoretical foundation and basic applications of CPS are systematically reviewed. In addition, the development of library and current research of CPS application in library management are presented. The vision and challenge of smart library are also discussed.Design/methodology/approachBy retrieving the main scholarly databases, the literature of CPS and its application in libraries were examined.FindingsThis study shows that a lot of CPS technology applications are still in initial stage, and explores CPS potential impacts on libraries.Originality/valueThe application of CPS in library management has not been paid much attention, this study provides a prospective for the application of CPS in libraries.

Context-aware energy-efficient applications for cyber-physical systems

Software systems have a strong impact on the energy consumption of the hardware they use. This is especially important for cyber-physical systems where power consumption strongly influences the battery life. For this reason, software developers should be more aware of the energy consumed by their systems. Moreover, software systems should be developed to adapt their behavior to minimize the energy consumed during their execution. This can be done by monitoring the usage context of the system and having runtime support to react to those changes that impact the energy footprint negatively. Although both the hardware and the software parts of cyber-physical systems can be adapted to reduce its energy consumption, this paper focuses on software adaptation. Concretely, the paper illustrates how to address the problem of developing context-aware energy-efficient applications using a Green Eco-Assistant that makes use of advanced software engineering methods, such as Dynamic Software Product Lines and Separation of Concerns. The main steps of our approach are illustrated by applying them to a cyber-physical system case study.

Cyber–physical perspective on smart grid design and operation

Emerging computation and communication technologies ubiquitously deployed in smart grids introduce unprecedented opportunities by enabling vigorous development of innovative business models and applications that aim for improving system efficiency, reliability, resiliency, and interoperability. Smart grids are typical cyber–physical systems (CPSs). The heterogeneous and complex nature of smart grids presents significant challenges introduced by the tight coupling of computation, communication, and physical systems. Here, the authors first provide an overview of smart grids from a CPS perspective. Then, the authors discuss the opportunities and challenges in smart grid design and operation. Next, a co-design framework is introduced and used for designing wide-area damping controller as one of many CPS applications that can be abstracted from various power system layers. The authors conclude that developing a theoretical modelling framework is critical for understanding and managing the complexity and interoperability of smart grids.

Quality-of-user-experience: a position paper

So far, research on quality-of-experience (QoE) has mostly been carried out in the area of multimedia communications, and user experience (UX) has addressed hedonic and pragmatic usage aspects of interactive applications. In the case of QoE, the meaningfulness of the application to the user and the forces driving the use have been largely neglected, while in the UX field, respective research has been carried out but hardly been incorporated in a model combined with the pragmatic and hedonic aspects. In this article, we take a step further approaching a comprehensive view of QoE and UX by adding eudaimonic aspects, such as meaningfulness and purpose-of-use, and by introducing the multidimensional construct of quality-of-user-experience (QUX). As meaning can be expected to play a major role in cyber-physical system (CPS) applications, we provide a characterization of CPS applications considering the professional/industrial and consumer/private domains, and analyze a number of characteristics that are relevant for users and their experience. In three exemplary scenarios, we illustrate the application of our concept and propose respective, not yet validated, QUX-models. Finally, we address related research challenges .

A simulation platform for human-machine interaction safety analysis of cyber-physical systems

Human-machine interaction (HMI) safety for cyber-physical systems (CPSs) is critical and its analysis is mandatory in many domains such as SCADA, autonomous cars, and medical devices. Generation of dynamic accident scenarios is the cornerstone of safety analysis. This paper presents a platform and associated methodology to effectively generate accident scenarios by modeling HMI errors using model-level fault injection, followed by simulation to produce dynamic evolutions of accident scenarios. An HMI fault tree template is proposed to guide the simulation. Results show that human mode confusion triggered by false displays may lead to severe accidents. Run-time assertions play a crucial role to detect HMI errors. A case study is described. The methodology expands Ptolemy II's modeling and simulation capabilities for CPS applications.

Resilient End-to-End Message Protection for Cyber-Physical System Communications

Cyber-physical system (CPS) communications for safely and effectively operating a mission-critical infrastructure must be securely protected to prevent the infrastructure from becoming vulnerable. The protection scheme used must be resilient and light-weighted for CPS field devices having constrained computing and communicating resources, and also scalable for control servers associating with a large number of the field devices. In addition, CPS applications such as smart metering require end-to-end privacy protection. However, as shown in this paper, none of conventional security schemes comprehensively meets the above requirements; group security schemes scale well for a massive number of devices but are weak in terms of privacy protection and resilience; point-to-point security schemes such as IPsec inherently have resilience but are limited to address scalability and thinness requirements. Motivated by the limitations of conventional security schemes, we design new group security scheme, resilient end-to-end message protection (REMP), exploiting the following notions: long-term keys per-node that are given by REMP authentication server, encryption keys per message sent that are probabilistically derived from a long-term key, and end-to-end authenticators per message sent that consist of a message sender's identity and a message authentication code. Compared with conventional group security schemes, we improve end-to-end security strength in terms of confidentiality, integrity, message source authentication, and key exposure resilience, while preserving scalability and extensibility.

Digital twin technology – An approach for Industrie 4.0 vertical and horizontal lifecycle integration

Abstract Digital Twin technology is increasingly gaining importance for digitizing industry. Even if digital twin technology still needs fundamental research, its significance for industry has become very visible, as digital twin technology is a key success factor to professionalize Cyber-Physical Systems (CPS) applications. Industrie 4.0 as an initiative to increase industrial added value is based on establishing connectivity between CPS and to enable communication between CPS. The industrial application scenarios for Industrie 4.0 aim at vertical and horizontal lifecycle integration concepts where digital twin technology plays an important role. This contribution explains major concepts of Industrie 4.0 and derives the role of digital twin technology. Furthermore, digital twin approaches are presented and as well as the proposal to use the STEP-technology (Standard for the Exchange of Product Model Data, ISO 10303) as a fundamental basis for a comprehensive digital twin technology.

Efficient and Scalable Runtime Monitoring for Cyber–Physical System

Our reliance on cyber–physical systems (CPSs) is increasingly widespread, but scalable methods for the analysis of such systems remain a significant challenge. Runtime verification of CPSs provides a reasonable middle ground between formal verification and simulation approaches, but it comes with its own challenges. A runtime verification system must run directly on the deployed application. In the CPS domain, it is therefore critical that a runtime verification system exhibits low overhead and good scalability so that the verification does not interfere with the analyzed CPS application. In this paper, we introduce Brace , a runtime verification system whose focus is on ensuring these performance qualities for applications in the CPS domain. Brace strives to bound the computation overhead for CPS runtime verification while preserving a high level of monitoring accuracy in terms of the number of false positive and false negative reports. Brace is particularly suitable to systems in which scheduling is distributed across networked CPS components. We evaluate Brace to determine how effectively and efficiently it can detect injected errors in two existing real-life CPS applications with distributed scheduling. Our results demonstrate that Brace efficiently detects those errors and a few true bugs and is able to bound both the memory and computation overhead even in systems with large numbers of observed events.

Massive MIMO for Industrial Internet of Things in Cyber-Physical Systems

To apply cyber-physical system (CPS) technique in industrial internet, a wireless technology that is able to robustly maintain hyperconnectivity between a data center and distributed user entities and/or industrial Internet of Things devices is required. We investigate the feasibility of utilizing massive multiple-input multiple-output (MIMO) as such a wireless technology. We analyze the performance of a massive MIMO base station deployed at a data center to provide massive connectivity to a large number of devices. In addition, we discuss related research challenges for deploying massive MIMO in industrial internet applications of CPS, such as device scheduling and power control, energy efficient design and radio frequency energy transfer/harvesting, signaling techniques for drones and mobile robots, and applications of underwater industrial internet.