Towards Creation of a Reference Architecture for Trust-Based Digital Ecosystems

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Authors

CIOROAICA Emilia CHREN Stanislav KUHN Thomas BÜHNOVÁ Barbora DIMITROV Dimitar

Year of publication 2019
Type Article in Proceedings
Conference Proceedings of European Conference on Software Architecture (ECSA 2019) Workshops
MU Faculty or unit

Faculty of Informatics

Citation
Doi http://dx.doi.org/10.1145/3344948.3344973
Keywords Collaborative Embedded Systems; Reference Architecture; Digital Ecosystems; Software Ecosystems; Smart Ecosystems; Automotive Smart Ecosystem; Smart Grid
Description With progressing digitalization and the trend towards autonomous computing, systems tend to form digital ecosystems, where each autonomous system aims at achieving its own goals. Within a highway ecosystem, for example, autonomous vehicles could deploy smart agents in the form of software applications. This would enable cooperative driving and ultimately formation of vehicle platoons that reduce air friction and fuel consumption. In the smart grid domain, software-defined virtual power plants could be established to enable remote and autonomous collaboration of various units, such as smart meters, data concentrators, and distributed energy resources, in order to optimize power generation, demand-side energy and power storage. Effective collaboration within these emerging digital ecosystems strongly relies on the assumption that all components of the ecosystem operate as expected, and a level of trust among them is established based on that. In this paper, we present the idea of trust-based digital ecosystems, built upon the concept of a digital twin of this ecosystem, as a machine readable representation of the system and a representation of goals and trust at runtime. This creates demand for introducing a reference architecture for trust-based digital ecosystems that would capture their main concepts and relationships. By modeling the goals of the actors and systems, a reference architecture can provide a basis for analyzing competitive forces that influence the health of an ecosystem.
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