The Internet of Simulation: Enabling agile model based systems engineering for cyber-physical systems

Abstract

Abstract-The expansion of the Internet of Things (IoT) has resulted in a complex cyber-physical system of systems that is continually evolving. With ever more complex systems being developed and changed there has been an increasing reliance on simulation as a vital part of the design process. There is also a growing need for simulation integration and co-simulation in order to analyse the complex interactions between system components. To this end, we propose that the Internet of Simulation (IoS), as an extension of IoT, can be used to meet these needs. The IoS allows for multiple heterogeneous simulations to be integrated together for co-simulation. It's effect on the engineer process is to facilitate agile practices without sacrificing rigour. An Industry 4.0 example case study is provided showing how IoS could be utilised.

Designing Socially and Organizationally Sustainable Industry 4.0 Systems: Requirements for Modeling Approaches

“…Clement et al [54], Salehi [57], Salehi and Wang [58], Mrugalska and Ahmed [59], Kayabay et al [60], Santos et al [61] In the remainder of this section, the ways in which the literature addresses the four principles are elaborated.…”

“…Working (i.e., executable) systems are implicitly assumed in the many accounts of iterative development characterized by early production and testing of prototypes. While additive manufacturing is widely accepted as a key technology for rapid prototyping in the I4.0 context, a lot of potential is also seen in virtual approaches [38,41,47,[51][52][53][54]. These approaches range from the use of app mockups, simple paper storyboards [47] and process simulations [50,53,54] to 3D-realistic virtual factories [52].…”

Survey of advances and challenges in intelligent autonomy for distributed cyber‐physical systems

“…This result in the benefit of being able to construct large co‐simulations from component simulations of parts and mitigates the difficulty of developing large‐scale monolithic simulations [18, 120]. Additionally, this allows individual system to be developed in a more agile way, responding faster to changes in requirements new environments [22]. The ability to readily compose detailed simulations is of particular importance for intelligent systems, especially if they augment existing systems as the additions can be extensively tested as virtual prototypes before deployment.…”

“…There are a number of challenges to the implementation of IoS and its wide use in intelligent autonomous systems. The problem of automated simulation integration is a particular challenge [22, 122]. Integrating an arbitrary collection of simulations remains infeasible for a number of reasons including: differing levels of fidelity, incompatible data types or representations, incompatible timesteps, or solvers.…”

“…Specifically from a service‐oriented architecture (SOA) perspective [20, 21], the services and micro‐services may be hardware systems or devices, human individuals, Cloud hosted software [software as a service (SaaS)], or even simulations (SIMaaS). The aggregation or composition of these services into workflows and subsequently, the workflows into services will provide a scalable approach to design and augmenting existing systems [22, 23].…”