Deep Reinforcement Learning Based Joint Allocation Scheme in a TWDM-PON-Based mMIMO Fronthaul Network by Yuansen Cheng, Yingjie Shao, Shifeng Ding, Chun-Kit Chan

“…The proposed scheme couples the heuristic radio resource allocation algorithm with the RL-based wavelength allocation model to optimize the fronthaul bandwidth, radio resource, and wavelength utilization efficiencies jointly in the downstream direction. …”
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An Improved Dingo Optimization for Resource Aware Scheduling in Cloud Fog Computing Environment by Santhosh Kumar Medishetti, Ganesh Reddy Karri

“…Task scheduling in Cloud-Fog computing environments is a critical aspect of optimizing resource allocation and enhancing performance. This study presents an improved version of the Dingo Optimization Algorithm (IDOA) specifically designed for task scheduling in Cloud-Fog computing. …”
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Communication‐awareness adaptive resource scheduling strategy for multiple target tracking in a multiple radar system by Yang Su, Ziyang Cheng, Zishu He, Minglong Deng

“…Abstract In this study, a communication‐awareness adaptive resource scheduling (CARS) strategy for multiple target tracking in a multiple radar system (MRS) is proposed. …”
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Optimization of Bandwidth Allocation and UAV Placement in Active RIS-Assisted UAV Communication Networks with Wireless Backhaul by Thi-Thuy-Minh Tran, Binh-Minh Vu, Oh-Soon Shin

“…The proposed design aims to maximize the achievable sum rate of all networks by jointly optimizing UAV placement; resource management strategies; transmit power allocation; and ARIS reflection coefficients, subject to backhaul constraints and power budget limitations in the ARIS system. …”
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Resource Scheduling in MU-MIMO and NOMA Enabled Integrated Access and Backhaul Networks by Chuan-Wei Cho, Meng-Shiuan Pan

“…The designed two-phase algorithm has the following features: 1) support for multi-path routing and efficient resource utilization through the combined use of MU-MIMO and NOMA, 2) a novel route decision phase that selects optimal paths by considering load balancing among IAB nodes, and 3) a dynamic link scheduling phase that allocates transmission power and schedules links to maximize network capacity. …”
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Feature selection using a multi-strategy improved parrot optimization algorithm in software defect prediction by Qi Fei, Guisheng Yin, Zhian Sun

“…The proposed approaches in this study hold significant practical value, particularly in improving software quality, optimizing testing resource allocation, and reducing maintenance costs, offering broad potential for application in real-world software engineering scenarios.…”
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A novel research on network security situation prediction based on iteratively optimized RBF-NN by Yuqin Wu, Congqi Shen, Shungen Xiao, Wei Feng, Yexian Fan, Xiuzhuang Zhou

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Resource Optimization Method Based on Spatio-Temporal Modeling in a Complex Cluster Environment for Electric Vehicle Charging Scenarios by Hongwei Wang, Wei Liu, Chenghui Wang, Kao Guo, Zihao Wang

“…In intelligent cluster systems, the spatio-temporal complexity of agent data collection and resource allocation, as well as the problems in collaborative organizations, present substantial challenges to efficient resource distribution. …”
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Interference-Aware AAV-TBS Coordinated NOMA: Joint User Scheduling, Power Allocation and Trajectory Design by Haiyong Zeng, Rui Zhang, Xu Zhu, Yufei Jiang, Zhongxiang Wei, Fu-Chun Zheng

“…We propose an autonomous aerial vehicle (AAV)-terrestrial base station (TBS) coordinated non-orthogonal multiple access (NOMA) scheme where AAV as an air BS coordinates with TBS to serve the users at cell edge via coordinated multi-point, and investigate its resource allocation problem for interference management and system performance enhancement. …”
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A study of parameter aggregation algorithms for virtual power plant terminal decentralized resource scheduling characteristics in alpine regions by Yan Wang, Ruizhi Zhang, Ying Wang, Wen Xiang, Lu Wang

“…Abstract To address the “secondary dispatch” problem in alpine virtual power plants caused by uncertainties in decentralized resource allocation, we develop an algorithm for aggregating dispatch parameters of distributed resources to achieve real-time load-demand matching. …”
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Enhancing Information Freshness and Energy Efficiency in D2D Networks Through DRL-Based Scheduling and Resource Management by Parisa Parhizgar, Mehdi Mahdavi, Mohammad Reza Ahmadzadeh, Melike Erol-Kantarci

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Long-term planning optimisation of sustainable energy systems: A systematic review and meta-analysis of trends, drivers, barriers, and prospects by Soheil Mohseni, Alan C. Brent

“…The long-term planning and optimisation of renewable and sustainable energy systems is indispensable for the efficient allocation of finite resources, especially in the context of the growing deployment of localised and distributed energy generation systems. …”
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A downlink resource scheduling strategy for C-RAN backhaul network by WANG Ru-yan, ZHOU Jing, WU Da-peng

“…According to the network demand of wireless users in hot spots, three optimization objectives including the number of used wavelengths, load balance, and well-distribution of real-time traffic were considered in the optimization of adaptive-weighted parallel genetic algorithm. Thus, the wavelength resources were dynamically allocated and resource utilization was improved. …”
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Multi-resource joint management strategy for 5 G network slicing based on POMDP by Yale Li

“…Such processes are capable of perceiving changes in network topology and dynamically adjusting resource allocation to adapt to constantly changing network conditions. …”
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Radio frequency energy harvesting-combined collaborative energy-saving computation offloading mechanism by Bei TANG, Qian WANG, Siguang CHEN

“…In order to fit the differentiated energy demands in vertical markets and ensure that internet of things (IoT) devices can hold an efficient and sustainable operation mode, a radio frequency energy harvesting-combined collaborative energy-saving computation offloading mechanism was studied.Specifically, a system energy consumption minimization problem was formulated under the joint optimization consideration of computation offloading decision, uplink bandwidth resource allocation, downlink bandwidth resource allocation and base station power splitting.Meanwhile, by combining the concept of penalty function, a new evaluation index was introduced, and then an adaptive particle swarm optimization-based collaborative energy saving computation offloading (APSO-CESCO) algorithm was proposed to solve the problem.The proposed algorithm constructed dynamic inertia weight and linearly adjusted penalty factor, which could alternate the spatial distribution density of the particle community in real-time during the iterative search process, and the optimal computation offloading policy with tolerable punishment could be well-generated.Furthermore, to prevent particles from exceeding exploration range, the velocity boundary was introduced which could also reduce the generation probability of invalid solutions and improve the actual exploration effectiveness.Finally, the simulation results show that the proposed algorithm can achieve higher convergence efficiency and solution accuracy, and compared with other common benchmark schemes, the system energy consumption can be reduced by 34.09%, 14.72%, and 6.86%, respectively.…”
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Two-Stage Energy Storage Allocation Considering Voltage Management and Loss Reduction Requirements in Unbalanced Distribution Networks by Hu Cao, Lingling Ma, Guoying Liu, Zhijian Liu, Hang Dong

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Interference Management in UAV-Assisted Multi-Cell Networks by Muchen Jiang, Honglin Ren, Yongxing Qi, Ting Wu

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SELECTIVE-PERMUTATIONAL METHOD FOR SOLVING PROBLEMS ON PARALLEL DISTRIBUTION OF TASKS AMONG PERFORMERS: SINGLE PERMUTATIONS by Rudolf A. Neydorf

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Mathematical Models for Management Information Systems on Digital Platforms: from Resource Management to Demand Forecasting by Viktor Godliuk

“…Particular attention is paid to mathematical approaches to load balancing, resource allocation, and platform scalability. The application of graph theory to analyze the relationships between users, content, and services, as well as Dijkstra and Floyd-Warshell algorithms for optimal data routing, is described. …”
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Regression-based investigation of latency in automated networks by Urooj Khan, Tariq Soomro, M.N. Brohi

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