Traffic Prediction Based on Online Vehicle Position Information for Simulation, Validation and Controller Resource Allocation Purposes by Rebeka Anna Jáger, Géza Szabó

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Communication resource allocation method in vehicular networks based on federated multi-agent deep reinforcement learning by Qingli Liu, Yongjie Ma

“…Abstract In highly dynamic vehicular networking scenarios, when Vehicle-to-Infrastructure links and Vehicle-to-Vehicle links share spectrum resources, the traditional distributed resource allocation method lacks global optimization and fails to respond to environmental changes in a timely manner, which leads to low spectral efficiency of the system. …”
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Dynamic Beam Hopping Algorithm for LEO Satellite Systems Based on User Grouping by Qing SHU, Weibiao LI, Zuolin JIN, Zhong ZHENG, Yongbo ZHANG, Zesong FEI

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Implications of algorithmic bias in AI-driven emergency response systems by Katsiaryna Bahamazava

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Energy optimization using adaptive control algorithm to enhance the performance of SDN_IOT environment by I. Varalakshmi, M. Thenmozhi

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Information Bottleneck-Based Domain Adaptation for Hybrid Deep Learning in Scalable Network Slicing by Tianlun Hu, Qi Liao, Qiang Liu, Georg Carle

“…We propose pre-training a variational information bottleneck (VIB)-based Quality of Service (QoS) estimator, using slice-specific inputs shared across all source domain slices. Each target domain slice can deploy this estimator to predict its QoS and optimize slice resource allocation using the IDLA algorithm. …”
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Edge computing smart grid resource scheduling algorithm based on reinforcement learning by Jinghang YU, Yichen ZHAO, Hu SONG

“…A smart grid is a power network capable of intelligent management and optimization.Network virtualization technology can effectively improve the resource utilization and reliability of smart grids and meet the differentiated needs of different users.In the case of limited resources, traditional virtual network embedding algorithms cannot dynamically adjust the allocation and mapping of virtual resources according to the resource usage and user needs of the power system.To solve this problem, edge computing and virtualization technology was combined and a virtual network resource scheduling algorithm based on reinforcement learning was introduced.The simulation results show that the proposed virtual resource scheduling algorithm is better than the other three scheduling algorithms in improving power grid reliability and resource utilization.…”
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ML-RASPF: A Machine Learning-Based Rate-Adaptive Framework for Dynamic Resource Allocation in Smart Healthcare IoT by Wajid Rafique

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Joint Optimization of Cache Placement and Bandwidth Allocation in Heterogeneous Networks by Weiqi Sun, Yong Li, Chunjing Hu, Mugen Peng

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Cost Minimization with Project Crashing: Comparison of the Traditional Solution and Genetic Algorithm Approach by Sadik Yıgıt, Semih Caglayan

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A Task Offloading and Resource Allocation Strategy Based on Multi-Agent Reinforcement Learning in Mobile Edge Computing by Guiwen Jiang, Rongxi Huang, Zhiming Bao, Gaocai Wang

“…Task offloading and resource allocation is a research hotspot in cloud-edge collaborative computing. …”
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Energy Aware Optimal Resource Allocation in Backhaul Constraint Wireless Networks: A Two Base Stations Scenario by Yuan Gao, Peng Xue, Yi Li, Hongyi Yu, Xianfeng Wang, Shihai Gao

“…Simulations show that this allocation algorithm can improve the system capacity and energy efficiency significantly compared with the blind alternatives.…”
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Energy-Efficient Multi-Agent Deep Reinforcement Learning Task Offloading and Resource Allocation for UAV Edge Computing by Shu Xu, Qingjie Liu, Chengye Gong, Xupeng Wen

“…This paper proposes a novel multi-agent reinforcement learning framework, termed Multi-Agent Twin Delayed Deep Deterministic Policy Gradient for Task Offloading and Resource Allocation (MATD3-TORA), to optimize task offloading and resource allocation in UAV-assisted MEC networks. …”
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Power-Efficient UAV Positioning and Resource Allocation in UAV-Assisted Wireless Networks for Video Streaming with Fairness Consideration by Zaheer Ahmed, Ayaz Ahmad, Muhammad Altaf, Mohammed Ahmed Hassan

“…The joint optimization includes power minimization, efficient resource allocation, i.e., transmit power and bandwidth, and efficient two-dimensional positioning of the UAV while meeting system constraints. …”
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Network Resource Allocation Method Based on Awareness–Prediction Joint Compensation for Low-Earth-Orbit Satellite Networks by Hang Di, Tao Dong, Zhihui Liu, Shuotong Wei, Qiwei Zhang, Dingyun Zhang

“…Furthermore, an efficient, accelerated alternating-direction method of multipliers (ADMM) resource allocation algorithm is proposed with the aim of maximizing the satisfaction of service resources requirements. …”
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Training efficiency optimization algorithm of wireless federated learning based on processor performance and network condition awareness by Guohao Pang, Xiaorong Zhu

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SPYDER: QoS-Aware Radio Resource Allocation in Multiuser ISAC-Capable C-V2X Networks by Syed Najaf Haider Shah, Aamir Ullah Khan, Christian Schneider, Joerg Robert

“…To counteract this, we employ sparse reconstruction algorithms within the compressed sensing framework, enhancing flexibility in TF resource allocation and providing high-resolution radar sensing despite uncoordinated resource selection. …”
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Mode selection and resource optimization for UAV-assisted cellular networks by Daquan FENG, Canjian ZHENG, Xiangqi KONG

“…The resource allocation and optimization scheme was studied in a coexistence scenario of unmanned aerial vehicle (UAV) and cellular communication network.To improve spectrum efficiency of the system, UAV users could reuse the cellular spectrum resources to access the network through full duplex or half duplex device-to-device technique.Additionally, a joint access control, mode selection, power control and resource allocation optimization problem was formulated to maximize the overall throughput of the network while ensuring quality of service requirements for both UAV users and ground cellular users.Specifically, the phase 1 method in the convex optimization was adopted for access control and feasibility check, and then the convex and concave procedure (CCCP) iterative algorithm was used to solve the power control problem for feasible UAV user pairs.By using this local optimum value, the original optimization problem can be simplified into a weighted maximization problem.Finally, the Kuhn-Munkres (KM) algorithm was used to match the optimal channel resources and obtain the global optimal throughput value of the system.Numerical results show that the proposed scheme can significantly improve the performance of system.…”
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Emergency task scheduling algorithm for space-based networks by LI Zheyuan, HE Lijun, JIA Ziye, LI Bokang, WANG Yanting, MIN Minghui

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Energy-saving computation offloading scheme based on Sarsa algorithm in industrial internet of things by Jun SUN, Shangweikang ZHAO

“…In order to reduce the total energy consumption of industrial internet of things systems with deadline requirements, a computing offloading scheme based on Sarsa algorithm was proposed.Based on the characteristics of Sarsa algorithm, the energy consumption optimization problem was coupled.The Sarsa algorithm iterated the external state value function, selected the appropriate edge computing server to offload the computing task, and then the particle swarm optimization algorithm solved the resource allocation problem.Finally, the environmental information was updated for the next round of algorithm iteration until the algorithm met the end conditions.The simulation results show that this scheme has faster convergence speed and effectively reduces the system energy consumption.…”
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