Related papers: Network Digital Twin: Context, Enabling Technologi…
In this paper, we propose a novel efficient digital twin (DT) data processing scheme to reduce service latency for multicast short video streaming. Particularly, DT is constructed to emulate and analyze user status for multicast group…
The concept of Digital Twin (DT) is increasingly applied to systems on different levels of abstraction across domains, to support monitoring, analysis, diagnosis, decision making and automated control. Whilst the interest in applying DT is…
Digital Twins are being used as an enabling technology in 6G applications across various domains, valued for their data-driven insights and real-time decision-making capabilities. However, integrating Digital Twins into 6G environments…
Unmanned aerial vehicles (UAVs) enhance coverage and provide flexible deployment in 5G and next-generation wireless networks. The performance of such wireless networks can be improved by developing new navigation and wireless adaptation…
The convergence of modeling & simulation (M&S) and artificial intelligence (AI) is leaving its marks on advanced digital technology. Pertinent examples are digital twins (DTs) - high-fidelity, live representations of physical assets, and…
With the accelerating availability of multimodal surgical data and real-time computation, Surgical Digital Twins (SDTs) have emerged as virtual counterparts that mirror, predict, and inform decisions across pre-, intra-, and postoperative…
Digital twins promise a better understanding and use of complex systems. To this end, they represent these systems at their runtime and may interact with them to control their processes. Software engineering is a wicked challenge in which…
Digital twins have been introduced as supporters to city operations, yet existing scene-descriptor formats and digital twin platforms often lack the integration, federation, and adaptable connectivity that urban environments demand. Modern…
This paper addresses the challenging problem of enabling reliable immersive teleoperation in scenarios where an Unmanned Aerial Vehicle (UAV) is remotely controlled by an operator via a cellular network. Such scenarios can be quite critical…
Resource slicing in low Earth orbit satellite networks (LSN) is essential to support diversified services. In this paper, we investigate a resource slicing problem in LSN to reserve resources in satellites to achieve efficient resource…
Digital Twin (DT) technology is far from being comprehensive and mature, resulting in their piecemeal implementation in practice where some functions are automated by DTs, and others are still performed by humans. This piecemeal…
Digital twins are transforming the way we monitor, analyze, and control physical systems, but designing architectures that balance real-time responsiveness with heavy computational demands remains a challenge. Cloud-based solutions often…
Achieving a holistic and long-term understanding through accurate network modeling is essential for orchestrating future networks with increasing service diversity and infrastructure complexities. However, due to unselective data collection…
This paper focuses on the feasibility of Deep Neural Operator (DeepONet) as a robust surrogate modeling method within the context of digital twin (DT) for nuclear energy systems. Through benchmarking and evaluation, this study showcases the…
As an emerging technology in the era of Industry 4.0, digital twin is gaining unprecedented attention because of its promise to further optimize process design, quality control, health monitoring, decision and policy making, and more, by…
The increasing relevance of resilience in wireless connectivity for Industry 4.0 stems from the growing complexity and interconnectivity of industrial systems, where a single point of failure can disrupt the entire network, leading to…
Digital Twins (DTs) systems are virtual representations of physical assets allowing organizations to gain insights and improve existing processes. In practice, DTs require proper modeling, coherent development and seamless deployment along…
The integration of machine learning tools into telecom networks, has led to two prevailing paradigms, namely, language-based systems, such as Large Language Models (LLMs), and physics-based systems, such as Digital Twins (DTs). While…
The increased use of software in the operation and management of telecommunication networks has moved the industry one step closer to realizing autonomous network operation. One consequence of this shift is the significantly increased need…
Smart Digital twins (SDTs) are being increasingly used to virtually replicate and predict the behaviors of complex physical systems through continual data assimilation enabling the optimization of the performance of these systems by…