Related papers: Hierarchical Digital Twin for Efficient 6G Network…
Motivated by climate change, increasing industrialization and energy reliability concerns, the smart grid is set to revolutionize traditional power systems. Moreover, the exponential annual rise in number of grid-connected users and…
The dramatic increase in the connectivity demand results in an excessive amount of Internet of Things (IoT) sensors. To meet the management needs of these large-scale networks, such as accurate monitoring and learning capabilities, Digital…
This article presents a vision where \textit{real-time} digital twins of the physical wireless environments are continuously updated using multi-modal sensing data from the distributed infrastructure and user devices, and are used to make…
The digital twins (DTs) of physical systems and environments enable real-time remote tracking, control, and learning, but require low-latency transmission of updates and sensory data to maintain alignment with their physical counterparts.…
In existing wireless networks, the control programs have been designed manually and for certain predefined scenarios. This process is complicated and error-prone, and the resulting control programs are not resilient to disruptive changes.…
Network slicing enables multiple virtual networks to be instantiated and customized to meet heterogeneous use case requirements over 5G and beyond network deployments. However, most of the solutions available today face scalability issues…
In this paper, we introduce a synergistic approach between artificial intelligence and system operators through an innovative digital twin architecture, integrated with an active learning framework, to enhance short-term load forecasting.…
This paper proposes an optimized Reconfigurable Internet of Things (RIoT) framework that integrates optical and radio wireless technologies with a focus on energy efficiency, scalability, and adaptability. To address the inherent complexity…
Wi-Fi networks increasingly suffer from performance degradation caused by contention-based channel access, dense deployments, and largely self-managed operation among mutually interfering access points (APs). In this paper, we propose a…
With the development of satellite communication technology, satellite-terrestrial integrated networks (STIN), which integrate satellite networks and ground networks, can realize seamless global coverage of communication services.…
We propose an adaptive control strategy for the simultaneous estimation of topology and synchronization in complex dynamical networks with unknown, time-varying topology. Our approach transforms the problem of time-varying topology…
With the arrival of the big data era, mobility profiling has become a viable method of utilizing enormous amounts of mobility data to create an intelligent transportation system. Mobility profiling can extract potential patterns in urban…
A Digital Twin (DT) may protect information that is considered private to its associated physical system. For a mobile device, this may include its mobility profile, recent location(s), and experienced channel conditions. Online schedulers,…
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…
Digital twin networks (DTNs) are real-time replicas of physical networks. They are emerging as a powerful technology for design, diagnosis, simulation, what-if-analysis, and artificial intelligence (AI)/machine learning (ML) driven…
The digital transformation of modern cities by integrating advanced information, communication, and computing technologies has marked the epoch of data-driven smart city applications for efficient and sustainable urban management. Despite…
Underwater acoustic sensor networks (UASNs) drive toward strong environmental adaptability, intelligence, and multifunctionality. However, due to unique UASN characteristics, such as long propagation delay, dynamic channel quality, and high…
Digital twins, as precise digital representations of physical systems, have evolved from passive simulation tools into intelligent and autonomous entities through the integration of artificial intelligence technologies. This paper presents…
This paper presents a novel approach for computing resource management of edge servers in vehicular networks based on digital twins and artificial intelligence (AI). Specifically, we construct two-tier digital twins tailored for vehicular…
Hybrid parallelism techniques are essential for efficiently training large language models (LLMs). Nevertheless, current automatic parallel planning frameworks often overlook the simultaneous consideration of node heterogeneity and dynamic…