Showing papers on "Systems architecture published in 2020"

A Survey of IoT Applications in Blockchain Systems: Architecture, Consensus, and Traffic Modeling

Abstract: Blockchain technology can be extensively applied in diverse services, including online micro-payments, supply chain tracking, digital forensics, health-care record sharing, and insurance payments. Extending the technology to the Internet of things (IoT), we can obtain a verifiable and traceable IoT network. Emerging research in IoT applications exploits blockchain technology to record transaction data, optimize current system performance, or construct next-generation systems, which can provide additional security, automatic transaction management, decentralized platforms, offline-to-online data verification, and so on. In this article, we conduct a systematic survey of the key components of IoT blockchain and examine a number of popular blockchain applications. In particular, we first give an architecture overview of popular IoT-blockchain systems by analyzing their network structures and protocols. Then, we discuss variant consensus protocols for IoT blockchains, and make comparisons among different consensus algorithms. Finally, we analyze the traffic model for P2P and blockchain systems and provide several metrics. We also provide a suitable traffic model for IoT-blockchain systems to illustrate network traffic distribution.

Underwater Internet of Things in Smart Ocean: System Architecture and Open Issues

Abstract: The development of the smart ocean requires that various features of the ocean be explored and understood. The Underwater Internet of Things (UIoT), an extension of the Internet of Things (IoT) to the underwater environment, constitutes powerful technology for achieving the smart ocean. This article provides an overview of the UIoT with emphasis on current advances, future system architecture, applications, challenges, and open issues. The UIoT is enabled by the most recent developments in autonomous underwater vehicles, smart sensors, underwater communication technologies, and underwater routing protocols. In the coming years, the UIoT is expected to bridge diverse technologies for sensing the ocean, allowing it to become a smart network of interconnected underwater objects that has self-learning and intelligent computing capabilities. This article first provides a horizontal overview of the UIoT. Then, we present a five-layer system architecture for the future UIoT, which consists of a sensing, communication, networking, fusion, and application layer. Finally, we suggest the current challenges and the future UIoT research trends, in which cloud computing, fog computing, and artificial intelligence are combined.

Blockchain-based life cycle assessment: An implementation framework and system architecture

Abstract: Life cycle assessment (LCA) is widely used for assessing the environmental impacts of a product or service. Collecting reliable data is a major challenge in LCA due to the complexities involved in the tracking and quantifying inputs and outputs at multiple supply chain stages. Blockchain technology offers an ideal solution to overcome the challenge in sustainable supply chain management. Its use in combination with internet-of-things (IoT) and big data analytics and visualization can help organizations achieve operational excellence in conducting LCA for improving supply chain sustainability. This research develops a framework to guide the implementation of Blockchain-based LCA. It proposes a system architecture that integrates the use of Blockchain, IoT, and big data analytics and visualization. The proposed implementation framework and system architecture were validated by practitioners who were experienced with Blockchain applications. The research also analyzes system implementation costs and discusses potential issues and solutions, as well as managerial and policy implications.

A generic tri-model-based approach for product-level digital twin development in a smart manufacturing environment

Abstract: Smart manufacturing, as an emerging manufacturing paradigm, leverages massive in-context data from manufacturing systems for intelligent decision makings. In such context, Cyber-Physical Systems (CPS) play a key role in digitizing manufacturing systems and integrating multiple systems together for collaborative works. Amongst different levels of smartness and connectedness of CPS, Digital Twin (DT), as an exact digital copy of a physical object or system including its properties and relationship with the environment, has a significant impact on realizing smart manufacturing. A DT constantly synchronizes with its physical system and provides real-time high-fidelity simulations of the system and offers ubiquitous control over the system. Despite its great advantages, few works have been discussed about DT reference models, let alone a generic manner to establish it for smart manufacturing. Aiming to fill the gap, this research introduces a generic CPS system architecture for DT establishment in smart manufacturing with a novel tri-model-based approach (i.e. digital model, computational model and graph-based model) for product-level DT development. The tri-model works concurrently to simulate real-world physical behaviour and characteristics of the digital model. To validate the proposed architecture and approach, a case study of an open source 3D printer DT establishment is further conducted. Conclusions and future works are also highlighted to provide insightful knowledge to both academia and industries at last.

Analysis of factors affecting IoT-based smart hospital design

Abstract: Currently, rapidly developing digital technological innovations affect and change the integrated information management processes of all sectors. The high efficiency of these innovations has inevitably pushed the health sector into a digital transformation process to optimize the technologies and methodologies used to optimize healthcare management systems. In this transformation, the Internet of Things (IoT) technology plays an important role, which enables many devices to connect and work together. IoT allows systems to work together using sensors, connection methods, internet protocols, databases, cloud computing, and analytic as infrastructure. In this respect, it is necessary to establish the necessary technical infrastructure and a suitable environment for the development of smart hospitals. This study points out the optimization factors, challenges, available technologies, and opportunities, as well as the system architecture that come about by employing IoT technology in smart hospital environments. In order to do that, the required technical infrastructure is divided into five layers and the system infrastructure, constraints, and methods needed in each layer are specified, which also includes the smart hospital’s dimensions and extent of intelligent computing and real-time big data analytic. As a result of the study, the deficiencies that may arise in each layer for the smart hospital design model and the factors that should be taken into account to eliminate them are explained. It is expected to provide a road map to managers, system developers, and researchers interested in optimization of the design of the smart hospital system.

A Framework Based on Distributed Ledger Technologies for Data Management and Services in Intelligent Transportation Systems

Abstract: Data are becoming the cornerstone of many businesses and entire systems infrastructure. Intelligent Transportation Systems (ITS) are no different. The ability of intelligent vehicles and devices to acquire and share environmental measurements in the form of data is leading to the creation of smart services for the benefit of individuals. In this paper, we present a system architecture to promote the development of ITS using distributed ledgers and related technologies. Thanks to these, it becomes possible to create, store and share data generated by users through the sensors on their devices or vehicles, while on the move. We propose an architecture based on Distributed Ledger Technologies (DLTs) to offer features such as immutability, traceability and verifiability of data. IOTA, a promising DLT for IoT, is used together with Decentralized File Storages (DFSes) to store and certify data (and their related metadata) coming from vehicles or by the users' devices themselves (smartphones). Ethereum is then exploited as the smart contract platform that coordinates the data sharing through access control mechanisms. Privacy guarantees are provided by the usage of distributed key management systems and Zero Knowledge Proof. We provide experimental results of a testbed based on real traces, in order to understand if DLT and DFS technologies are ready to support complex services, such as those that pertain to ITS. Results clearly show that, while the viability of the proposal cannot be rejected, further work is needed on the responsiveness of DLT infrastructures.

Healthy Operator 4.0: A Human Cyber-Physical System Architecture for Smart Workplaces.

Abstract: Recent advances in technology have empowered the widespread application of cyber–physical systems in manufacturing and fostered the Industry 4.0 paradigm. In the factories of the future, it is possible that all items, including operators, will be equipped with integrated communication and data processing capabilities. Operators can become part of the smart manufacturing systems, and this fosters a paradigm shift from independent automated and human activities to human–cyber–physical systems (HCPSs). In this context, a Healthy Operator 4.0 (HO4.0) concept was proposed, based on a systemic view of the Industrial Internet of Things (IIoT) and wearable technology. For the implementation of this relatively new concept, we constructed a unified architecture to support the integration of different enabling technologies. We designed an implementation model to facilitate the practical application of this concept in industry. The main enabling technologies of the model are introduced afterward. In addition, a prototype system was developed, and relevant experiments were conducted to demonstrate the feasibility of the proposed system architecture and the implementation framework, as well as some of the derived benefits.

Symbiotic human–robot collaborative approach for increased productivity and enhanced safety in the aerospace manufacturing industry

Abstract: Robots are perfect substitutes for skilled workforce on some repeatable, general, and strategically important tasks, but this substitution is not always feasible. Despite the evolution of robotics, some industries have been traditionally robot-reluctant because their processes involve large or specific parts and non-serialized products; thus, standard robotic solutions are not cost-effective. This work presents a novel approach for advanced manufacturing applied to the aerospace industry, combining the power and the repeatability of the robots with the flexibility of humans. The proposed approach is based on immersive and symbiotic collaboration between human workers and robots, presenting a safe, dynamic, and cost-effective solution for this traditionally manual and robot-reluctant industry. The proposed system architecture includes control, safety, and interface components for the new collaborative manufacturing process. It has been validated in a real-life case study that provides a solution for the manufacturing of aircraft ribs. The results show that humans and robots can share the working area simultaneously without physical separation safely, providing beneficial symbiotic collaboration and reducing times, risks, and costs significantly compared with manual operations.

System Architecture for Real-Time Surface Inspection Using Multiple UAVs

Abstract: This paper presents a real-time control system for surface inspection using multiple unmanned aerial vehicles (UAVs). The UAVs are coordinated in a specific formation to collect data of the inspecting objects. The communication platform for data transmission is based on the Internet of Things (IoT). In the proposed architecture, the UAV formation is established via using the angle-encoded particle swarm optimisation to generate an inspecting path and redistribute it to each UAV where communication links are embedded with an IoT board for network and data processing capabilities. Data collected are transmitted in real time through the network to remote computational units. To detect potential damage or defects, an online image processing technique is proposed and implemented based on histograms. Extensive simulation, experiments and comparisons have been conducted to verify the validity and performance of the proposed system.

Security and Privacy of Smart Home Systems Based on the Internet of Things and Stereo Matching Algorithms

Abstract: With the rapid development of the Internet of Things (IoT), security and privacy of smart home systems based on IoT are more and more popular. As the key component of IoT, wireless communication and sensor technology are prerequisites for the security and confidentiality of smart home systems. The smart home systems integrate electronic information technology and computer control. By designing and installing various sensors in the home for collecting data, and then using the IoT platform for data transmission, the remote control of the home running state can be realized. The home security is guaranteed. This article designs IoT architecture of smart home, and then hardware and software are designed according to the system architecture. The hardware part is mainly analyzed from the image recognition module and the speech recognition module. In addition, a stereo matching algorithm for smart video surveillance is proposed to optimize the accuracy of the surveillance system. Finally, the simulation results prove that the designed smart home systems have a low cost and high accuracy. It not only optimizes the performance of smart home systems but also improves the safety factor.

Evaluation of Reliability in Component-Based System Using Architecture Topology

Abstract: In the component-based software, as its name indicates, the overall system performance is a reflection of the performance of its components. The correct analysis of reliability, which is known as a critical factor in component-based software engineering process, is one of the necessary tasks in such a system. However, most of the previous studies do not provide a practical and complete approach on this issue of this field. So, the aim of this work is to introduce a new systematic approach for software reliability analysis. The system architecture is used by this approach for time-dependent reliability evaluation.

5G Radio Access Network Architecture for Terrestrial Broadcast Services

Abstract: The 3rd Generation Partnership Project (3GPP) has defined based on the Long Term Evolution (LTE) enhanced Multicast Broadcast Multimedia Service (eMBMS) a set of new features to support the distribution of Terrestrial Broadcast services in Release 14. On the other hand, a new 5th Generation (5G) system architecture and radio access technology, 5G New Radio (NR), are being standardized from Release 15 onwards, which so far have only focused on unicast connectivity. This may change in Release 17 given a new Work Item set to specify basic Radio Access Network (RAN) functionalities for the provision of multicast/broadcast communications for NR. This work initially excludes some of the functionalities originally supported for Terrestrial Broadcast services under LTE, e.g., free to air, receive-only mode, large-area single frequency networks, etc. This paper proposes an enhanced Next Generation RAN architecture based on 3GPP Release 15 with a series of architectural and functional enhancements, to support an efficient, flexible and dynamic selection between unicast and multicast/broadcast transmission modes and also the delivery of Terrestrial Broadcast services. The paper elaborates on the Cloud-RAN based architecture and proposes new concepts such as the RAN Broadcast/Multicast Areas that allows a more flexible deployment in comparison to eMBMS. High-level assessment methodologies including complexity analysis and inspection are used to evaluate the feasibility of the proposed architecture design and compare it with the 3GPP architectural requirements.

Systems Architecture Design Pattern Catalog for Developing Digital Twins

Abstract: A digital twin is a digital replica of a physical entity to which it is remotely connected. A digital twin can provide a rich representation of the corresponding physical entity and enables sophisticated control for various purposes. Although the concept of the digital twin is largely known, designing digital twins based systems has not yet been fully explored. In practice, digital twins can be applied in different ways leading to different architectural designs. To guide the architecture design process, we provide a pattern-oriented approach for architecting digital twin-based Internet of Things (IoT) systems. To this end, we propose a catalog of digital twin architecture design patterns that can be reused in the broad context of systems engineering. The patterns are described using the well-known documentation template and support the various phases in the systems engineering life cycle process. For illustrating the application of digital twin patterns, we adopt a case study in the agriculture and food domain.

Task Offloading Strategy Based on Reinforcement Learning Computing in Edge Computing Architecture of Internet of Vehicles

Abstract: With the rapid increase of vehicles, the explosive growth of data flow and the increasing shortage of spectrum resources, the performance of existing task offloading scheme is poor, and the on-board terminal can’t achieve efficient computing. Therefore, this article proposes a task offload strategy based on reinforcement learning computing in edge computing architecture of Internet of vehicles. Firstly, the system architecture of Internet of vehicles is designed. The Road Side Unit receives the vehicle data in community and transmits it to Mobile Edge Computing server for data analysis, while the control center collects all vehicle information. Then, the calculation model, communication model, interference model and privacy issues are constructed to ensure the rationality of task offloading in Internet of vehicles. Finally, the user cost function is minimized as objective function, and double-layer deep Q-network in deep reinforcement learning algorithm is used to solve the problem for real-time change of network state caused by user movement. The results show that the proposed offloading strategy can achieve fast convergence. Besides, the impact of user number, vehicle speed and MEC computing power on user cost is the least compared with other offloading schemes. The task offloading rate of our proposed strategy is the highest with better performance, which is more suitable for the scenario of Internet of vehicles.

IoT meets BPM: a bidirectional communication architecture for IoT-aware process execution

Abstract: Business processes are frequently executed within application systems that involve humans, computer systems as well as objects of the Internet of Things (IoT). Nevertheless, the usage of IoT technology for system supported process execution is still constrained by the absence of a common system architecture that manages the communication between both worlds. In this paper, we introduce an integrated approach for IoT-aware business process execution that exploits IoT for BPM by providing IoT data in a process-compatible way, providing an IoT data provenance framework, considering IoT data for interaction in a pre-defined process model, and providing wearable user interfaces with context-specific IoT data provision. The approach has been implemented on top of contemporary BPM modeling concepts and system technology. The introduced technique has evaluated extensively in different use cases in industry.

Integrated 5G-Satellite Networks: A Perspective on Physical Layer Reliability and Security

Abstract: Fifth generation (5G) mobile systems are expected to be integrated with different radio access methods such as satellite components to provide seamless connectivity and ubiquitous coverage for users worldwide. In this article, we first provide a brief review of current initiatives and system architecture for the convergence of satellite and 5G networks. Then, we investigate various approaches to improve reliability or security at the physical layer for the integrated 5G-satellite networks. An effective achievable rate is presented as the key performance indicator to measure the security and reliability trade-off, followed by the implementation of a proposed beamforming scheme. Finally, we present future trends and challenges in integrated 5G-satellite networks.

Software-Defined Edge Computing (SDEC): Principle, Open IoT System Architecture, Applications, and Challenges

Abstract: Edge computing is a bridge for realizing the convergence between physical space and cyber space in the Internet of Things (IoT) paradigm. Large numbers of physical objects produce a huge amount of data that needs to be efficiently processed in the edge side. This situation urgently requires novel ideas and framework in the design and management of edge computing to improve and enhance its performance. In this article, we propose an approach and principle of software-defined edge computing (SDEC) from the perspective of cyber-physical mapping, where the ultimate goal is to achieve a highly automatic and intelligent edge computing system. The SDEC can also help realize flexible management and intelligent collaboration among various edge hardware resources and services by way of software. To this end, we design an SDEC-based open IoT system architecture which decouples upper level IoT applications from the underlying physical edge resources and builds dynamically reconfigurable smart edge services. The software-definition mechanism of the SDEC platform is proposed to introduce the detailed processes that the underlying physical devices are defined in the form of software. We also describe an illustrative application case about smart factory to present the practical effectiveness of the proposed scheme. Finally, we outline several challenges which are worthy of in-depth study and research. The SDEC paradigm can share, reuse, recombine, and reconfigure edge resources and services so that the overall service capability of the edge side can be improved.

Parallel Internet of Vehicles: ACP-Based System Architecture and Behavioral Modeling

Abstract: Vehicles in Internet of Vehicles (IoV) exchange information about location, environment, infotainment, as well as social information with other units via vehicular communication networks. This makes IoV with key social entities in the human–vehicle–infrastructure–roadside units (RSUs) as integrated intelligent transportation systems. Therefore, by identifying the cyber–physical–social features of IoV and presenting its complexity issues of both engineering and social dimensions, this article proposes and introduces the concept, architecture, and applications of parallel IoV (PIoV). Three main components of PIoV are demonstrated, which are artificial IoV to learn and describe the physical IoV, computation experiments to evaluate and predict the consequences and values of driving strategies, and parallel execution to prescribe the operation of the physical IoV. PIoV makes it possible to achieve safe, smart, effective, and efficient transportation management and control. The final objective of PIoV is to equip IoV with descriptive, predictive, and prescriptive intelligence based on the parallel intelligence approach.

The Sky Is Not the Limit: A Visual Performance Model for Cyber-Physical Co-Design in Autonomous Machines

Abstract: We introduce the “Formula-1” (F-1) roofline model to understand the role of computing in aerial autonomous machines. The model provides insights by exploiting the fundamental relationships between various components in an aerial robot, such as sensor framerate, compute performance, and body dynamics (physics). F-1 serves as a tool that can aid computer and cyber-physical system architects to understand the optimal design (or selection) of various components in the development of autonomous machines.

SystemDS: A Declarative Machine Learning System for the End-to-End Data Science Lifecycle

Abstract: Machine learning (ML) applications become increasingly common in many domains. ML systems to execute these workloads include numerical computing frameworks and libraries, ML algorithm libraries, and specialized systems for deep neural networks and distributed ML. These systems focus primarily on efficient model training and scoring. However, the data science process is exploratory, and deals with underspecified objectives and a wide variety of heterogeneous data sources. Therefore, additional tools are employed for data engineering and debugging, which requires boundary crossing, unnecessary manual effort, and lacks optimization across the lifecycle. In this paper, we introduce SystemDS, an open source ML system for the end-to-end data science lifecycle from data integration, cleaning, and preparation, over local, distributed, and federated ML model training, to debugging and serving. To this end, we aim to provide a stack of declarative language abstractions for the different lifecycle tasks, and users with different expertise. We describe the overall system architecture, explain major design decisions (motivated by lessons learned from Apache SystemML), and discuss key features and research directions. Finally, we provide preliminary results that show the potential of end-to-end lifecycle optimization.

A Cognitively Inspired System Architecture for the Mengshi Cognitive Vehicle

Abstract: This paper introduces the functional system architecture of the Mengshi intelligent vehicle, winner of the 2018 World Intelligent Driving Challenge (WIDC). Different from traditional smart vehicles, a cognitive module is introduced in the system architecture to realise the transition from perception to decision-making. This is shown to enhance the practical utility of the smart vehicle, enabling safe and robust driving in different scenes. The collaborative work of hardware and software systems is achieved through multi-sensor fusion and artificial intelligence (AI) technologies, including novel use of deep machine learning and context-aware scene analysis to select optimal driving strategies. Experimental results using both robustness tests and road tests confirm that the Mengshi intelligent vehicle is reliable and robust in challenging environments. This paper describes the major components of this cognitively inspired architecture and discusses the results of the 2018 WIDC.

A Distributed Ledger Based Infrastructure for Smart Transportation System and Social Good

Abstract: This paper presents a system architecture to promote the development of smart transportation systems. Thanks to the use of distributed ledgers and related technologies, it is possible to create, store and share data generated by users through their sensors, while moving. In particular, IOTA and IPFS are used to store and certify data (and their related metadata) coming from sensors or by the users themselves. Ethereum is exploited as the smart contract platform that coordinates the data sharing and provisioning. The necessary privacy guarantees are provided by the usage of Zero Knowledge Proof. We show some results obtained from some use case scenarios that demonstrate how such technologies can be integrated to build novel smart services and to promote social good in user mobility.