Related papers: User-centric Service Provision for Edge-assisted M…
Digital Twins (DT) have become crucial to achieve sustainable and effective smart urban solutions. However, current DT modelling techniques cannot support the dynamicity of these smart city environments. This is caused by the lack of…
6G networks are envisioned to enable a wide range of applications, such as autonomous vehicles and smart cities. However, this rapid expansion of network topologies makes the management of 6G wireless networks more complex and leads to…
This paper investigates the transformative potential of digital twin (DT) technology for non-terrestrial networks (NTNs). NTNs, comprising airborne and space-borne elements, face unique challenges in network control, management, and…
We propose a digital twin-assisted adaptive preloading scheme to enhance bandwidth efficiency and user quality of experience (QoE) in short video streaming. We first analyze the relationship between the achievable throughput and video…
As a key technology in the 5G era, Mobile Edge Computing (MEC) has developed rapidly in recent years. MEC aims to reduce the service delay of mobile users, while alleviating the processing pressure on the core network. MEC can be regarded…
Multi-Access Edge Computing (MEC) will allow implementing low-latency services that have been unfeasible so far. The European Telecommunications Standards Institute (ETSI) and the 3rd Generation Partnership Project (3GPP) are working…
Digital Twin (DT) technology has become rather popular in recent years, promising to optimize production processes, manage the operation of cyber-physical systems, with an impact spanning across multiple application domains (e.g.,…
Digital twin (DT) technology can replicate physical entities in cyberspace. A mobility DT digitalizes connected and autonomous vehicles (CAVs) and their surrounding traffic environment, allowing to monitor the maneuvering and distribution…
Digital twin (DT) enables smart manufacturing by leveraging real-time data, AI models, and intelligent control systems. This paper presents a state-of-the-art analysis on the emerging field of DTs in the context of milling. The critical…
In this paper, we investigate a resource allocation and model retraining problem for dynamic wireless networks by utilizing incremental learning, in which the digital twin (DT) scheme is employed for decision making. A two-timescale…
This paper introduces a sensor steering methodology based on deep reinforcement learning to enhance the predictive accuracy and decision support capabilities of digital twins by optimising the data acquisition process. Traditional sensor…
Device-edge collaboration on deep neural network (DNN) inference is a promising approach to efficiently utilizing network resources for supporting artificial intelligence of things (AIoT) applications. In this paper, we propose a novel…
As the video streaming traffic in mobile networks is increasing, improving the content delivery process becomes crucial, e.g., by utilizing edge computing support. At an edge node, we can deploy adaptive bitrate (ABR) algorithms with a…
Accurate neuronavigation is essential for generating the intended effect with transcranial magnetic stimulation (TMS). Precise coil placement also directly influences stimulation efficacy. Traditional neuronavigation systems often rely on…
Edge Computing (EC) allows users to access computing resources at the network frontier, which paves the way for deploying delay-sensitive applications such as Mobile Augmented Reality (MAR). Under the EC paradigm, MAR users connect to the…
Mobile edge computing has become an effective and fundamental paradigm for futuristic autonomous vehicles to offload computing tasks. However, due to the high mobility of vehicles, the dynamics of the wireless conditions, and the…
Passive Optical Data Centre Networks have been developed due to the performance limitations in current data centres to provide high performance within data centre networks. An AWGR based passive optical network data centre architecture is…
In this paper, we investigate user equipment (UE)-radio access technology (RAT) association and bandwidth assignment to maximize sum-rates in a multi-RAT network. To this end, we formulate an optimization problem that jointly addresses UE…
This paper has proposed a Digital Twin (DT) framework for real-time motion and pose control of soft robotic grippers. The developed DT is based on an industrial robot workstation, integrated with our newly proposed approach for soft gripper…
Optimizing modern wireless networks is exceptionally challenging due to their high dynamism and complexity. While the agentic artificial intelligence (AI) powered by reinforcement learning (RL) offers a promising solution, its practical…