… twin network to build network topology and the stochastic task arrival model in IIoT systems.
Then, we formulate the stochastic computation … As the formulated problem is a stochastic …

… contains the network model, stochastic demand model, communication model, computing
model, queuing … We then present the problem formulation of Digital Twin Edge Networks. …

… the computing requirements. On the other hand, in an industrial manufacturing twin network,
… for stochastic computation offloading in digital twin networks,” IEEE Trans. Ind. Informat., vol. …

… stochastic modeling and performance analysis for iSDVNs and the uses of machine-learning
algorithms through digital twin networks (… routing protocols, stochastic computations, and …

… as the digital twin, is trained with data taken from a stochastic computational model. This
strategy allows the use of an interpretable model (physics-based) to build a fast digital twin (…

… a stochastic computation offloading problem to maximize the long-term time-averaged energy
efficiency, considering the network … Under stochastic behaviors and time-varying wireless …

… study proposes a stochastic actor–critic RL algorithm termed Twin actor Soft Actor–… twin-actor
framework in SAC for performance improvement, yielding an RL algorithm termed as twin …

… computation, it helps the network adapt to the stochastic task arrivals, the time-varying LEO
locations, the cloud server price, and the DT computation … optimize DT computation frequency…

… This paper proposes the use of artificial neural networks (ANN) in DES models to determine
… accurate modelling of stochastic behaviour. An application is in digital twin models that aim …

… ANT falls into a general class of robust computation techniques referred to as stochastic
computation, where signal and error statistics are consciously exploited to detect and correct …