On-the-Fly Computing Meets IoT Markets — Towards a Reference Architecture

Jazayeri, Bahar; Schwichtenberg, Simon

doi:10.1109/icsaw.2017.59

Cited by 7 publications

(4 citation statements)

References 16 publications

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“…Apart from the above discussed, there are different non-traditional CoT platforms available to provide dedicated Industrial IoT solutions like Axonize (Marletta, 2019), Afero(CAO & Gao, 2014), Comarch (Gazis, 2016), Conrad (Jazayeri & Schwichtenberg, 2017), Everything, Ixon, Factana (Ahlmeyer & Chircu, 2016). Table 4 shows the competencies of dif-…”

Section: Non-traditional Cot Platforms Used For Industry 40mentioning

confidence: 99%

Security issues and challenges in cloud of things-based applications for industrial automation

et al. 2023

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Due to the COVID-19 outbreak, industries have gained a thrust on contactless processing for computing technologies and industrial automation. Cloud of Things (CoT) is one of the emerging computing technologies for such applications. CoT combines the most emerging cloud computing and the Internet of Things. The development in industrial automation made them highly interdependent because the cloud computing works like a backbone in IoT technology. This supports the data storage, analytics, processing, commercial application development, deployment, and security compliances. Now amalgamation of cloud technologies with IoT is making utilities more useful, smart, service-oriented, and secure application for sustainable development of industrial processes. As the pandemic has increased access to computing utilities remotely, cyber-attacks have been increased exponentially. This paper reviews the CoT’s contribution to industrial automation and the various security features provided by different tools and applications used for the circular economy. The in-depth analysis of security threats, availability of different features corresponding the security issues in traditional and non-traditional CoT platforms used in industrial automation have been analysed. The security issues and challenges faced by IIoT and AIoT in industrial automation have also been addressed.

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Section: Non-traditional Cot Platforms Used For Industry 40mentioning

confidence: 99%

Security issues and challenges in cloud of things-based applications for industrial automation

et al. 2023

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“…support for IoT/CPS capabilities composition/decomposition through their enabled properties. The motivations include: a) the ability to address the composition of functional, business, human, trustworthiness, timing, data, boundaries, composition, and lifecycle concerns of an IoT or a CPS, and b) taking into consideration the complexity, discoverability, adaptability, and constructivity of the composite capabilities [38][39] [40]; c) enabling computation distribution of computation-intensive services running in cloud nodes to low computation nodes at the Fog/Edge level [252]; d) addressing composite services functional and qualitative properties during runtime to enable flexible and adaptable compositions [42] and e) incorporating composition-friendly ontologies and composition mechanisms in distributed environments through hierarchical structures such as classes and subclasses [35][36] [220]; f) providing automatic composition mechanisms to build modular software capabilities and from heterogeneous service marketplaces and locations [37] [221] [222] [223] [225]; g) enabling reusability of small, atomic, reusable components through decomposition [252] [252] [29]; and h) guiding atomic service discovery, selection, and complex services prototyping and composition in the cloud environments [252] [41] [40]. Figure 12 summarizes the motivations above.…”

Section: Data Training and Compositionmentioning

confidence: 99%

“…This also requires the installation of different Microsoft Azure components and command line capabilities. A rule-based cloud solution, IFTTT [37], has also been presented as a cloud composition service. Users can set sensing or actuation rules anywhere on their apps, and the IFTTT service composes the desired rules or outcomes.…”

Section: ) Aq5: What Are the Different Stakeholders' Categories And C...mentioning

confidence: 99%

IoT Capabilities Composition and Decomposition: A Systematic Review

et al. 2023

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As billions of IoT devices join the Internet, researchers and innovators increasingly explore IoT capabilities achieved via service composition or reuse of existing capabilities via service decomposition. Many systematic literature reviews (SLRs) were produced on this subject; however, two issues remain to be addressed: i) a reference taxonomy of the different aspects of IoT capabilities composition and decomposition is needed, and ii) many formal questions (e.g., standards role, formal representations applications, state-space explosion countermeasures, etc.), technical questions (e.g., composition process types and automation levels synergies, service decomposition categories, the role of AI/ML, etc.), and QoS questions (e.g., privacy, interoperability, and scalability challenges and solutions, etc.) remain unanswered. We introduce this work by discussing notions of IoT capabilities composition and decomposition in a layered IoT architecture while highlighting the strengths and weaknesses of existing SLRs. We identify unanswered questions through gaps in related work and motivate these questions using the PICOC methodology. We explain the search methodology and organize the topic questions using the proposed reference taxonomy. The identified research questions are answered, and trends and gaps that need additional attention from the research community are highlighted. This effort benefits city planners and end-users of IoT systems as it contributes to a better understanding of the role of composition and decomposition of IoT capabilities in building valueadded services or reusing existing ones for resource optimization. For researchers, this effort contributes a reference taxonomy for the topic and sheds light on important questions while highlighting corresponding trends and gaps requiring further attention.

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“…OpenPnP relies on standardized industry models in the process automation domain to allow for vendor‐neutral interoperability. Another IoT reference architecture was designed to connect software services for IoT applications, exemplified by IFTTT‐applications . For OpenPnP, we assume a more constrained interplay of services, but could extend into this direction in the future …”

Section: Related Workmentioning

confidence: 99%

Automated industrial IoT‐device integration using the OpenPnP reference architecture

et al. 2019

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Distributed control systems are currently evolving towards industrial Internet of Things (IoT) systems communicating fully using Internet protocols. This creates opportunities for streamlining costly commissioning processes, which today require substantial manual work for installing, configuring, and integrating thousands of actuators and sensors. The vision of "plug-and-produce" control systems has been pursued for more than 15 years, but existing approaches fell short regarding configuration tasks and vendor neutrality. This paper introduces the standards-based IoT reference architecture OpenPnP, which allows largely automating the configuration and integration tasks of industrial commissioning processes. The architecture includes a number of design and technology decisions and the required implementation can be scaled down to resource-constrained industrial devices. This paper demonstrates how OpenPnP can reduce configuration and integration efforts up to 90% in typical settings, while potentially scaling well up to tens of thousands of communicated signals. Practitioners can orient their implementations towards OpenPnP, therefore potentially enabling "plug-and-produce" in many thousands of control systems. KEYWORDS client-server systems, control engineering, Internet of Things, real-time systems, software architecture 246 of these tasks include a number of manually executed steps done by engineers, for example, the device identification, device wiring, entering configuration parameters, and interaction fine-tuning between devices, the control system, and workstations. Many of these tasks are even more complicated due to the lack of standardized parameter models, legacy communication interfaces, and proprietary software tools requiring profound knowledge and expertise. Hence, the entire process of commissioning a plant or a process including thousands or ten thousands of devices may last several calendar months, costing millions of dollars. [3][4][5] Taking this into account, there is a high interest from customer side to simplify the commissioning process. 6 Therefore, researchers and practitioners have been working on "plug and produce" (PnP) approaches in the last two decades. 7,8 They simplify the process for commissioning a device in process automation similar to the installation and usage of devices for consumer computers, so called "plug and play." Transferring this concept to the process automation world is complicated because such an PnP approach needs to be implemented on different levels in operation, starting from device level up to plant or even enterprise level. Existing proposals for PnP approaches 9-13 often focus on low-level network discovery of industrial field devices but neglect higher-level configuration and integration tasks, which cause most manual efforts. Especially, for PnP on the device level, network discovery of industrial field devices is only one task of many. The industrial field devices also need standardized and self-describing information models so that no additional informa...

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On-the-Fly Computing Meets IoT Markets — Towards a Reference Architecture

Cited by 7 publications

References 16 publications

Security issues and challenges in cloud of things-based applications for industrial automation

Security issues and challenges in cloud of things-based applications for industrial automation

IoT Capabilities Composition and Decomposition: A Systematic Review

Automated industrial IoT‐device integration using the OpenPnP reference architecture

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