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ISSN: 2352-8648
CN: 50-1212/TN
p-ISSN: 2468-5925

APFed: Adaptive personalized federated learning for intrusion detection in maritime meteorological sensor networks

With the rapid development of advanced networking and computing technologies such as the Internet of Things, network function virtualization, and 5G infrastructure, new development opportunities are...

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UAV-assisted MEC offloading strategy with peak AOI boundary optimization: A method based on DDQN

In response to the requirements for large-scale device access and ultra-reliable and low-latency communication in the power internet of things, unmanned aerial vehicle-assisted multi-access edge computing...

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Robust beamforming design for energy harvesting efficiency maximization in RIS-aided SWIPT system

This paper investigates Energy Harvesting Efficiency (EHE) maximization problems for Reconfigurable intelligent surface (RIS) aided Simultaneous Wireless Information and Power Transfer (SWIPT). This...

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Game-theoretic private blockchain design in edge computing networks

Considering the privacy challenges of secure storage and controlled flow, there is an urgent need to realize a decentralized ecosystem of private blockchain for cyberspace. A collaboration dilemma arises...

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Rate distortion optimization for adaptive gradient quantization in federated learning

Federated Learning (FL) is an emerging machine learning framework designed to preserve privacy. However, the continuous updating of model parameters over uplink channels with limited throughput leads...

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Multi-layer network embedding on scc-based network with motif

Interconnection of all things challenges the traditional communication methods, and Semantic Communication and Computing (SCC) will become new solutions. It is a challenging task to accurately detect,...

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Short video preloading via domain knowledge assisted deep reinforcement learning

Short video applications like TikTok have seen significant growth in recent years. One common behavior of users on these platforms is watching and swiping through videos, which can lead to a significant...

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RS-DRL-based offloading policy and UAV trajectory design in F-MEC systems

For better flexibility and greater coverage areas, Unmanned Aerial Vehicles (UAVs) have been applied in Flying Mobile Edge Computing (F-MEC) systems to offer offloading services for the User Equipment...

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Partial observation learning-based task offloading and spectrum allocation in UAV collaborative edge computing

Capable of flexibly supporting diverse applications and providing computation services, the Mobile Edge Computing (MEC)-assisted Unmanned Aerial Vehicle (UAV) network is emerging as an innovational...

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Practical frequency-hopping MIMO joint radar communications: design and experiment

Joint Radar and Communications (JRC) can implement two Radio Frequency (RF) functions using a single of resources, providing significant hardware, power and spectrum savings for wireless systems requiring...

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FedACT: an adaptive chained training approach for federated learning in computing power networks

Federated Learning (FL) is a novel distributed machine learning methodology that addresses large-scale parallel computing challenges while safeguarding data security. However, the traditional FL model...

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Cost-aware cloud workflow scheduling using DRL and simulated annealing

Cloud workloads are highly dynamic and complex, making task scheduling in cloud computing a challenging problem. While several scheduling algorithms have been proposed in recent years, they are mainly...

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IoT data analytic algorithms on edge-cloud infrastructure: A review

The adoption of Internet of Things (IoT) sensing devices is growing rapidly due to their ability to provide real-time services. However, it is constrained by limited data storage and processing power....

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A deep learning driven hybrid beamforming method for millimeter wave MIMO system

The hybrid beamforming is a promising technology for the millimeter wave MIMO system, which provides high spectrum efficiency, high data rate transmission, and a good balance between transmission performance...

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A novel fractional uplink power control framework for self-organizing networks

Internet of things and network densification bring significant challenges to uplink management. Only depending on optimization algorithm enhancements is not enough for uplink transmission. To control...

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The deep spatiotemporal network with dual-flow fusion for video-oriented facial expression recognition

The video-oriented facial expression recognition has always been an important issue in emotion perception. At present, the key challenge in most existing methods is how to effectively extract robust...

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Software defined intelligent satellite-terrestrial integrated networks: Insights and challenges

Satellite-Terrestrial integrated Networks (STNs) have been advocated by both academia and industry as a promising network paradigm to achieve service continuity and ubiquity. However, STNs suffer from...

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Opportunistic admission and resource allocation for slicing enhanced IoT networks

Network slicing is envisioned as one of the key techniques to meet the extremely diversified service requirements of the Internet of Things (IoT) as it provides an enhanced user experience and elastic...

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Towards reinforcement learning in UAV relay for anti-jamming maritime communications

Maritime communications with sea surface reflections and sea wave occlusions are susceptible to jamming attacks due to the wide geographical area and intensive wireless communication services. Unmanned...

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Internet of robotic things for mobile robots: Concepts, technologies, challenges, applications, and future directions

Nowadays, Multi Robotic System (MRS) consisting of different robot shapes, sizes and capabilities has received significant attention from researchers and are being deployed in a variety of real-world...

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Autonomous machine learning for early bot detection in the internet of things

The high costs incurred due to attacks and the increasing number of different devices in the Internet of Things (IoT) highlight the necessity of the early detection of botnets (i.e., a network of infected...

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Adaptive delay-energy balanced partial offloading strategy in Mobile Edge Computing networks

Mobile Edge Computing (MEC)-based computation offloading is a promising application paradigm for serving large numbers of users with various delay and energy requirements. In this paper, we propose...

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Smart all-time vision: The battery-free video communication for urban administration and law enforcement

The Chinese government is dedicated to enhancing the level of informatization in administrative law enforcement to ensure fairness and increase credibility. Currently, law enforcement has exposed such...

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Joint computation offloading and resource allocation in vehicular edge computing networks

Vehicular Edge Computing (VEC) is a promising technique to accommodate the computation-intensive and delay-sensitive tasks through offloading the tasks to the RoadSide-Unit (RSU) equipped with edge...

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Scheduling optimization for upstream dataflows in edge computing

Edge computing can alleviate the problem of insufficient computational resources for the user equipment, improve the network processing environment, and promote the user experience. Edge computing is...

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