Litcius/Paper detail

A Flexible and Modular Architecture for Edge Digital Twin: Implementation and Evaluation

Marco Picone, Marco Mamei, Franco Zambonelli

2022ACM Transactions on Internet of Things67 citationsDOIOpen Access PDF

Abstract

IoT systems based on Digital Twins (DTs) — virtual copies of physical objects and systems — can be very effective to enable data-driven services and promote better control and decisions, in particular by exploiting distributed approaches where cloud and edge computing cooperate effectively. In this context, digital twins deployed on the edge represents a new strategic element to design a new wave of distributed cyber-physical applications. Existing approaches are generally focused on fragmented and domain-specific monolithic solutions and are mainly associated to model-driven, simulative or descriptive visions. The idea of extending the DTs role to support last-mile digitalization and interoperability through a set of general purpose and well-defined properties and capabilities is still underinvestigated. In this paper, we present the novel Edge Digital Twins (EDT) architectural model and its implementation, enabling the lightweight replication of physical devices providing an efficient digital abstraction layer to support the autonomous and standard collaboration of things and services. We model the core capabilities with respect to the recent definition of the state of the art, present the software architecture and a prototype implementation. Extensive experimental analysis shows the obtained performance in multiple IoT application contexts and compares them with that of state-of-the-art approaches.

Topics & Concepts

Computer scienceCloud computingInteroperabilityDistributed computingArchitectureEnhanced Data Rates for GSM EvolutionModular designEdge computingDomain (mathematical analysis)Software engineeringComputer architectureOperating systemTelecommunicationsArtVisual artsMathematical analysisMathematicsIoT and Edge/Fog ComputingDigital Transformation in IndustryModular Robots and Swarm Intelligence