A generic service oriented software platform to design ambient intelligent systems

Lavirotte, Stéphane; Rey, Gaëtan; Rocher, Gérald; Tigli, Jean‐Yves

doi:10.1145/2800835.2800843

Cited by 4 publications

(3 citation statements)

References 5 publications

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“…A bootstrap is a basic executable program on a device, or a run-time environment, which the system in charge of the deployment rely on (e.g., Docker engine). Approaches such as Calvin run-time [28], WComp [27], or D-LITE [10], D-NR [24] all rely on their specific run-time environment where mechanisms such as dynamic component loading or class loading are typically used. There is a lack of addressing the trustworthy aspects and advanced support in the deployment and orchestration of the IoT.…”

Section: On the Deployment At The Device Layermentioning

confidence: 99%

4. Model-based Continuous Deployment of SIS

Ferry¹,

Song²,

Dautov³

et al. 2021

DevOps for Trustworthy Smart IoT Systems

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Section: On the Deployment At The Device Layermentioning

confidence: 99%

4. Model-based Continuous Deployment of SIS

Ferry¹,

Song²,

Dautov³

et al. 2021

DevOps for Trustworthy Smart IoT Systems

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“…A bootstrap is a basic executable program on a device, or a run-time environment, which the system in charge of the deployment rely on (e.g., Docker engine). Approaches such as Calvin run-time [MBS + 17], WComp [LRRT15], or D-LITE [CGDLR11], D-NR [GBLL15] all rely on their specific run-time environment where mechanisms such as dynamic component loading or class loading are typically used. Contrary to these approaches, GeneSIS does not rely on a specific bootstrap but instead leverage common run-time environments such as Docker, Node.js, SSH.…”

Section: Related Workmentioning

confidence: 99%

Continuous Deployment of Trustworthy Smart IoT Systems.

Ferry¹,

Nguyen²,

Song³

et al. 2020

JOT

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While the next generation of IoT systems need to perform distributed processing and coordinated behaviour across IoT, Edge and Cloud infrastructures, their development and operation are still challenging. A major challenge is the high heterogeneity of their infrastructure, which broadens the surface for security attacks and increases the complexity of maintaining and evolving such complex systems. In this paper, we present our approach for Generation and Deployment of Smart IoT Systems (GeneSIS) to tame this complexity. GeneSIS leverages model-driven engineering to support the DevSecOps of Smart IoT Systems (SIS). More precisely, GeneSIS includes: (i) a domain specific modelling language to specify the deployment of SIS over IoT, Edge and Cloud infrastructure with the necessary concepts for security and privacy; and (ii) a models@run.time engine to enact the orchestration, deployment, and adaptation of these SIS. The results from our smart building case study have shown that GeneSIS can support security by design from the development (via deployment) to the operation of IoT systems and back again in a DevSecOps loop. In other words, GeneSIS enables IoT systems to keep up security and adapt to evolving conditions and threats while maintaining their trustworthiness.

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“…Many works have been dedicated to advance the adaptation domain [4]; frameworks [2] [5] [6], methods and techniques [3] [7] [8] [9], principles [10] [11] have already been proposed. However, most of these information focus on solving problems of system at runtime and they do not provide any solution to separate concerns and responsiveness in dynamic context-aware system.…”

Section: Introductionmentioning

confidence: 99%

Intermediate Common Model—The Solution to Separate Concerns and Responsiveness in Dynamic Context-Aware System

Rey

Tigli

Lavirotte

et al. 2017

JCC

Self Cite

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Nowadays, many works are interested in adapting to the context without taking into account neither the responsiveness to adapt their solution, nor the ability of designers to model all the relevant concerns. Our paper provides a new architecture for context management that tries to solve both problems. This approach is also based on the analysis and synthesis of context-aware frameworks proposed in literature. Our solution is focus on a separation of contextual concerns at the design phase and preserves it as much as possible at runtime. For this, we introduce the notion of independent views that allow designers to focus on their domain of expertise. At runtime, the architecture is splitted in 2 independent levels of adaptation. The highest is in charge of current context identification and manages each view independently. The lowest handles the adaptation of the application according to the rules granted by the previous level.

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A generic service oriented software platform to design ambient intelligent systems

Cited by 4 publications

References 5 publications

4. Model-based Continuous Deployment of SIS

4. Model-based Continuous Deployment of SIS

Continuous Deployment of Trustworthy Smart IoT Systems.

Intermediate Common Model—The Solution to Separate Concerns and Responsiveness in Dynamic Context-Aware System

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