Symbiotic CPS Design-Space Exploration through Iterated Optimization

Yu, Sheng-Jung; Incer, Inigo; Prabhu, Valmik; Chattoraj, Anwesha; Vin, Eric; Fremont, Daniel J.; Mehta, Amita; Sangiovanni-Vincentelli, A.; Sastry, S. Shankar; Seshia, Sanjit A.

doi:10.1145/3576914.3587525

Cited by 2 publications

(2 citation statements)

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“…Ref. [1] presents a symbiotic design methodology aimed at facilitating CPS design processes through collaboration between designers and optimization tools. This methodology efficiently discovers unconventional designs while optimizing design objectives.…”

Section: Related Workmentioning

confidence: 99%

“…At the heart of this transformation lie Cyber-Physical Systems (CPSs), which seamlessly integrate physical components with computational and communication capabilities to monitor, control, and optimize various aspects of urban life. In recent years, the concept of Symbiotic CPSs [1][2][3] has gained traction, signifying a paradigm shift towards collaborative and mutually beneficial interactions between heterogeneous CPSs within Smart City environments. Unlike traditional CPSs, which often operate in "silos" with predefined functions and data formats, Symbiotic CPSs embrace diversity in both data and infrastructure, fostering interoperability and synergy among disparate systems.…”

Section: Introductionmentioning

confidence: 99%

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Smart City as Cooperating Smart Areas: On the Way of Symbiotic Cyber–Physical Systems Environment

Tricomi,

Giacobbe,

Ficili

et al. 2024

Sensors

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The arising of the Cyber–Physical Systems’ vision and concepts drives technological evolution toward a new architectural design for the infrastructure of an environment referred to as a Smart Environment. This perspective alters the way systems within Smart City landscapes are conceived, designed, and ultimately realized. Modular architecture, resource-sharing techniques, and precise deployment approaches (such as microservices-oriented or reliant on the FaaS paradigm) serve as the cornerstones of a Smart City cognizant of multiple Cyber–Physical Systems composing it. This paper presents a framework integrating Digital Decisioning, encompassing the automated combination of human-derived knowledge and data-derived knowledge (e.g., business rules and machine learning), to enhance decision-making processes and application definition within the Smart City context.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%