Smart Cyber Physical Systems from the Software Engineering Perspective (sCPS-SE)

A special issue of Computers (ISSN 2073-431X).

Deadline for manuscript submissions: closed (15 November 2019) | Viewed by 12836

Special Issue Editors


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Guest Editor
Department of Engineering, Robert Morris University, Moon Township, PA 15108, USA
Interests: distributed systems; middleware; software engineering; Healthcare 4.0; smart systems; CPS and IoT/IIoT
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Middleware Technologies Lab., Pittsburgh, PA 15057, USA
Interests: middleware; fog computing; cloud computing; software engineering; cyber-physical systems; unmanned aerial vehicles; smart healthcare systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This is an invitation to contribute to this Special Issue and make your mark in this growing and extremely important field of software engineering for smart Cyber Physical Systems (sCPS).

Smart means “having or showing a quick-witted intelligence.” In a system or software, the key becomes defining what intelligence is. In general, a smart system is one that is capable of making the right decisions at the right time and adapting to the results. In CPS, we have many of the required components to achieve smartness: Sensors provide the necessary observations and data; software components to understand the data; and actuators to apply the necessary actions. All of this is designed in a closed feedback loop for continuous operations. Making CPS smart requires introducing more sophisticated capabilities to the software components to enable advanced analytics and intelligent functions that can respond effectively and efficiently to different situations. This introduces the need for more storage and processing power in such systems. Therefore, the limited capabilities of the CPS components become a prohibiting factor. As a result, we need to integrate more powerful resources such as the cloud to enable large scale storage and high performance processing. Collected data can be transferred to the cloud, which stores and analyze them to make intelligent decisions that are then passed back to the CPS components for action. Moreover, we can utilize fog and edge nodes to support sCPS systems by providing more localized features for systems that require real-time functionality, mobility and localization support.

The high volume of data, real-time requirements, multiple levels of integration and interoperations all lead to great challenges when designing and developing sCPS applications for any domain. As a result, it becomes critical to address these issues in a more formalized manner through the proper application of software engineering principles. In this Special Issue, we would like to highlight the importance of software engineering processes and tools to facilitate sCPS applications development. Work related to software development lifecycle and processes, requirements engineering, verification and validation, deployment and operations, to name some examples is welcome. Application of these principles within specific application domains like manufacturing, healthcare, transportation and many more are also encouraged. The following is a sample list of relevant areas; however, other relevant areas in this context are welcome:

  • Software development processes for sCPS applications
  • sCPS Software development life cycle models, issues and management
  • Multi-paradigm modeling in sCPS
  • Inter-disciplinary approaches for building sCPS applications
  • Architectural design approaches for sCPS
  • Software-based reliability and availability of sCPS
  • Integration challenges for sCPS systems and components
  • Interoperation issues across platforms and components for sCPS
  • sCPS software requirements engineering
  • Verification and validation procedures and tools for sCPS applications
  • Deployment and operational challenges of sCPS systems
  • Managing uncertainties and emergent behaviors in sCPS environments
  • Standardization efforts for sCPS software components
  • Integration of cloud and fog computing with sCPS systems
  • Addressing specific sCPS software requirements like mobility, localization and real-time processing
  • Incorporating intelligent software in sCPS applications
  • Integrating big data analytics tools and algorithms for sCPS applications
  • Addressing software security issues in sCPS systems
  • Scalability of sCPS applications
  • Software design and development of domain specific sCPS applications such as:
    • Smart manufacturing and Industry 4.0
    • Smart healthcare systems
    • Smart grids and utility systems
    • Smart energy management systems
    • Smart transportation systems
    • Smart city applications
    • Smart home systems

Papers in the above or relevant topics in software engineering for sCPS are welcome. Both original research contributions and review papers will be considered for publication. Please make sure you follow the MDPI Computer submission instructions when you prepare your papers.

Dr. Jameela Al-Jaroodi
Dr. Nader Mohamed
Guest Editors

Manuscript Submission Information

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Keywords

  • CPS
  • sCPS
  • Smart CPS Applications
  • Middleware
  • Integration
  • Software Engineering
  • Software Development Process
  • Software Architecture
  • Software Development Tools
  • Cloud Computing
  • Fog/Edge Computing
  • Intelligent algorithms
  • Data analytics algorithms

Published Papers (2 papers)

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Research

20 pages, 2171 KiB  
Article
The Harvest Coach Architecture: Embedding Deviation-Tolerance in a Harvest Logistic Solution
by Hugo Daniel Macedo, René Søndergaard Nilsson and Peter Gorm Larsen
Computers 2019, 8(2), 31; https://doi.org/10.3390/computers8020031 - 23 Apr 2019
Cited by 6 | Viewed by 5247
Abstract
We introduce a deviation-tolerance software architecture, which is devised for a prototype of a cloud-based harvest operation optimisation system issuing harvest plans. The deviation-tolerance architecture adapts the fault tolerance notions originating in the area of systems engineering to the harvest domain and embeds [...] Read more.
We introduce a deviation-tolerance software architecture, which is devised for a prototype of a cloud-based harvest operation optimisation system issuing harvest plans. The deviation-tolerance architecture adapts the fault tolerance notions originating in the area of systems engineering to the harvest domain and embeds them into the Vienna developed method (VDM) model at the core of our harvest logistics system prototype. The fault tolerance supervision/execution level architecture is framed under the notion of an “harvest coach” which diagnoses deviations to the planned operations using “harvest deviation monitors” and deploys a novel “plan” (controller) that mitigates the encountered “deviation” (fault). The architecture enabled the early start of field experiments of the harvest logistics system prototype, which lead to the validation/refutation of early design stage assumptions on the diverse system components behaviours and capabilities. For instance, we casually found discrepancies in the arithmetic precision of open-source libraries used in the conversion of vehicle positioning coordinates, we assessed the maturity of the frameworks used to develop the field user interfaces, and we calibrated the level of system-operator interactivity when deviations occurs. The obtained results indicate that the architecture may have a positive impact in the context of developing systems featuring intrinsic human-driven deviations which require mitigation. Full article
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16 pages, 4116 KiB  
Article
Failure Detection and Prevention for Cyber-Physical Systems Using Ontology-Based Knowledge Base
by Nazakat Ali and Jang-Eui Hong
Computers 2018, 7(4), 68; https://doi.org/10.3390/computers7040068 - 06 Dec 2018
Cited by 34 | Viewed by 7129
Abstract
Cyber-physical systems have emerged as a new engineering paradigm, which combine the cyber and physical world with comprehensive computational and analytical tools to solve complex tasks. In cyber-physical systems, components are developed to detect failures, prevent failures, or mitigate the failures of a [...] Read more.
Cyber-physical systems have emerged as a new engineering paradigm, which combine the cyber and physical world with comprehensive computational and analytical tools to solve complex tasks. In cyber-physical systems, components are developed to detect failures, prevent failures, or mitigate the failures of a system. Sensors gather real-time data as an input to the system for further processing. Therefore, the whole cyber-physical system depends on sensors to accomplish their tasks and the failure of one sensor may lead to the failure of the whole system. To address this issue, we present an approach that utilizes the Failure Modes, Effects, and Criticality Analysis, which is a prominent hazard analysis technique to increase the understanding of risk and failure prevention. In our approach, we transform the Failure Modes, Effects, and Criticality Analysis model into a UML(Unified Modeling Language) class diagram, and then a knowledge base is constructed based on the derived UML class diagram. Finally, the UML class diagram is used to build an ontology. The proposed approach employs a 5C architecture for smart industries for its systematic application. Lastly, we use a smart home case study to validate our approach. Full article
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