Cyber-physical microservices: An IoT-based framework for manufacturing systems

Thramboulidis, Kleanthis; Vachtsevanou, Danai C.; Solanos, Alexandros

doi:10.1109/icphys.2018.8387665

Cited by 63 publications

(31 citation statements)

References 38 publications

(58 reference statements)

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“…More recently, Velasquez [21] surveyed the state-of-theart on orchestration beyond services in cloud computing, but also addressing the Internet of Everything and fog computing paradigms. The work of Thramboulidis et al [22] also falls into that category. They propose an IoT-based framework for manufacturing systems that allows manufacturing plant processes to be defined as compositions of primitive cyberphysical microservices adopting either the orchestration or the choreography pattern.…”

Section: B Orchestration and Choreography Of Distributed Manufacturimentioning

confidence: 99%

Robust Digital Twin Compositions for Industry 4.0 Smart Manufacturing Systems

Preuveneers

Joosen

Ilie‐Zudor

2018

2018 IEEE 22nd International Enterprise Distributed Object Computing Workshop (EDOCW)

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Industry 4.0 is an emerging business paradigm that is reaping the benefits of enabling technologies driving intelligent systems and environments. By acquiring, processing and acting upon various kinds of relevant context information, smart automated manufacturing systems can make wellinformed decisions to adapt and optimize their production processes at runtime. To manage this complexity, the manufacturing world is proposing the 'Digital Twin' model to represent physical products in the real space and their virtual counterparts in the virtual space, with data connections to tie the virtual and real products together for an augmented view of the manufacturing workflow. The benefits of such representations are simplified process simulations and efficiency optimizations, predictions, early warnings, etc. However, the robustness and fidelity of digital twins are a critical concern, especially when independently developed production systems and corresponding digital twins interfere with one another in a manufacturing workflow and jeopardize the proper behavior of production systems. We therefore evaluate the addition of safeguards to digital twins for smart cyber-physical production systems (CPPS) in an Industry 4.0 manufacturing workflow in the form of feature toggles that are managed at runtime by software circuit breakers. Our evaluation shows how these improvements can increase the robustness of interacting digital twins by avoiding local errors from cascading through the distributed production or manufacturing workflow.

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Section: B Orchestration and Choreography Of Distributed Manufacturimentioning

confidence: 99%

Robust Digital Twin Compositions for Industry 4.0 Smart Manufacturing Systems

Preuveneers

Joosen

Ilie‐Zudor

2018

2018 IEEE 22nd International Enterprise Distributed Object Computing Workshop (EDOCW)

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“…Each microservice operates as an independent function, offering access to its internal logic and data through network interfaces and defined APIs. MSA are widely used in the industry for applications where scalability, resiliency, and availability are required, as is the case for Netflix 1 and Uber 2 (among others). Recently, Internet of Things (IoT) [1]- [3] and network virtualization [4] applications started adopting this paradigm.…”

Section: Introductionmentioning

confidence: 99%

Enhancing microservices architectures using data-driven service discovery and QoS guarantees

Houmani

Balouek-Thomert

Caron

et al. 2020

2020 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGRID)

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Microservices promise the benefits of services with an efficient granularity using dynamically allocated resources. In the current evolving architectures, data producers and consumers are created as decoupled components that support different data objects and quality of service. Actual implementations of service meshes lack support for data-driven paradigms, and focus on goal-based approaches designed to fulfill the general system goal. This diversity of available components demands the integration of users requirements and data products into the discovery mechanism. This paper proposes a data-driven service discovery framework based on profile matching using data-centric service descriptions. We have designed and evaluated a microservices architecture for providing service meshes with a standalone set of components that manages data profiles and resources allocations over multiple geographical zones. Moreover, we demonstrated an adaptation scheme to provide quality of service guarantees. Evaluation of the implementation on a real life testbed shows effectiveness of this approach with stable and fluctuating request incoming rates.

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“…Microservice the micro application is different from SOA and promises to change the way for the software development and service deployment style. Microservices are the basic building block of the microservice architecture that is one of the latest architectural upcoming trends in software development industry and promising to address several challenging issues in software development methodology [2]. Microservice architecture (MSA) is a famous architectural development style adopted by world-wide Internet services such as Netflix, Amazon and eBay.…”

Section: Introductionmentioning

confidence: 99%

Efficient Hybrid Research for QoS-Aware Microservice Composition

Singhal¹,

Usha²,

Raj³

2019

IJRTE

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Recent advances in the E-business enable the evolution of software development paradigms. MSA is emerging as an alternative approach to SOA and claiming to resolve various challenges in the software development mechanism. Microservices can be implemented as an independent module for software development. In the growing business era, the user requirement is complex and dynamic. User dynamic requirement is a challenge and cannot be completed by a single microservice hence there is a need of service composition in order to fulfill user dynamic business-related queries. For the appropriate service selection, QoS ontology semantic annotation is performed. There are two service composition methods are available i.e. orchestration and choreography. In this paper, we proposed an effective and efficient hybrid approach for the service composition.

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Cyber-physical microservices: An IoT-based framework for manufacturing systems

Cited by 63 publications

References 38 publications

Robust Digital Twin Compositions for Industry 4.0 Smart Manufacturing Systems

Robust Digital Twin Compositions for Industry 4.0 Smart Manufacturing Systems

Enhancing microservices architectures using data-driven service discovery and QoS guarantees

Efficient Hybrid Research for QoS-Aware Microservice Composition

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