Showing 201 - 220 results of 1,377 for search '(( resources allocation algorithm ) OR ( sources allocation algorithm ))', query time: 0.18s Refine Results
  1. 201

    Blockchain-Empowered UAV-Assisted Computation Resource Allocation in Smart Farm Services Platform by Sida Huang, Matilda Isaac, Yuan Gao, Yuji Dong, Jie Zhang, Bintao Hu

    Published 2025-01-01
    “…To minimise the total service delay (which includes the transmission delay and processing delay) among the user equipment (UEs) and UAVs, we propose jointly optimising the communication resource allocation for all UEs and UAVs, the computation resource allocation at each UAV, and the transmission power. …”
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  2. 202

    Dynamic resource allocation scheme for multiuser OFDM–UWB systems based on user's rate by Chao CHENG, Zhi-hong QIAN, Chun-lan LI, Xue WANG

    Published 2012-09-01
    “…According to original dynamic resource allocation algorithms,a new dynamic resource allocation algorithm for multiuser OFDM-UWB system based on users'rates was proposed to minimize the total transmitting power whil sa-tisfy requests for QoS and data rate of all users.Qual ty of the system was improved running the subcarrier allocation and bit allocation algorithms based on fairness of users.In subcarrier allocation process,rate impact factor was used to com-pare influence of different subcarriers to a user.In allocation process,bits were allocated to each user's subcarriers first,then bits on each subcarriers were adjusted according to rate request of each user.In or to reduce the complexity system of the furthermore,a subcarrier and bit allocation scheme is employed through subcarrier grouping.Simulation results indicate that the algorithm can lower power consume,BER and operation complexity.…”
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  3. 203

    Service aware base station processing resource allocation for centralized radio access network by Xinping ZHANG, Yuanyuan WANG, Lin TIAN, Shuliang HAO

    Published 2018-08-01
    “…Current research on resource allocation algorithmsmainly focuses on data centers,and cloud computing environments.These resource allocation algorithms did not consideRthe diversity of processing resources(CPU,memory,network bandwidth,FPGA,DSP)and the diversity of service types in the centralized base station,resulting in the low processing resource utilization.In ordeRto solve this problem,a service oriented base station processing resource allocation algorithm was proposed.Firstly,the Fisher partitionmethod was used to classify the base station’s processing resource requirements according to the user’s service request.Then,the resource allocation balancing strategy was used to allocate the base station processing resources.Experimental results show that the algorithm is effective to reduce the number of physi cal servers and improves the resource utilization of the servers,realizing energy conservation and communications.…”
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  4. 204

    Resource Allocation of Multi-Satellite Beam Hopping Technology Based on System Capacity Maximization by Qing SHU, Xiaoning ZHANG, Zesong FEI

    Published 2022-12-01
    “…Unlike medium and high earth orbit satellites, LEO satellites have the characteristics of small path loss, low propagation delay and high deployment fl exibility.LEO satellites are widely used in real time services, global internet of things, emergency communication and other fi elds.In order to solved the problems of large diff erences in service demand distribution of terrestrial users and low resource utilization in LEO satellite communication systems, a resource allocation algorithm of LEO multi-satellite beam hopping technology based on convex optimization was proposed, which aimed to maximized the system capacity.For multisatellite beam hopping scenarios in LEO satellite communication system, the beam-hopping technology could fl exibly allocated system resources accorded to user needs.Considered the factor of co-channel interference, the service region division scheme based on load balancing and the inter-satellite resource allocation priority scheme was proposed.In order to improved system capacity and resource utilization, it jointly designed a time and power resource allocation algorithm based on convex optimization.The simulation results showed that the proposed scheme could eff ectively reduced co-channel interference and realized the ondemand allocation of system capacity without causing waste of resources.…”
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  5. 205

    Joint scheduling and resource allocation based on reinforcement learning in integrated access and backhaul networks by Joeun Kim, Youngil Jeon, Junhwan Lee, Moon-Sik Lee, Taesoo Kwon

    Published 2025-06-01
    “…Because of the inherent nature of IAB, access and backhaul links share the same resource pool causing cross-link interference. To address this challenge, this paper investigates an algorithm based on reinforcement learning (RL) for joint scheduling and resource allocation (RA) problem, aiming to mitigate interference and enhance user data rates. …”
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  6. 206

    Optimizing resource allocation in industrial IoT with federated machine learning and edge computing integration by Ala'a R. Al-Shamasneh, Faten Khalid Karim, Yu Wang

    Published 2025-09-01
    “…The study explores resource allocation in Federated Machine Learning (FedML) for the Industrial Internet of Things (IIoT), focusing on efficient and privacy-conscious data processing. …”
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  7. 207
  8. 208

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

    Published 2024-01-01
    “…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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  9. 209

    Opportunistic spectrum sharing protocol and optimal resource allocation based on OFDM cooperation relaying by Wei-dang LU, Xuan-li WU, Xue-jun SHA, Nai-tong ZHANG

    Published 2012-11-01
    “…An opportunistic spectrum sharing protocol based on OFDM cooperation relaying was proposed.When the primary user experiences weak channel conditions,it could not achieve its target rate.If the cognitive user could help the primary user achieve its target rate,it accessed the pectrum of the primary user in the cooperation way.In this access way,the cognitive user used a fraction of the subcarriers to amplify-and-forward the signal of the primary user,to help the primary user achieve its target rate.And uses the remained subcarriers to transmit its own signal.The resource allocation was analyzed in this cooperation way.An optimal resource allocation algorithm based on dual ethod was proposed,which maximized the rate of the cognitive user while g anteeing the primary user achieve its target rate.If the cognitive user could not help the primary user achieve its target rate,to make use the spectrum efficiently,the cognitive user accessed the spectrum of the primary user in the non-cooperation way,and uses the whole accessed spectrum to transmit its own signal.The simulation demonstrates the efficiency of the proposed spectrum sharing protocol as well as its benefit to both primary and cognitive user.…”
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  10. 210

    Energy-Efficient Resource Allocation in Mobile Edge Computing Using NOMA and Massive MIMO by Qusay Alghazali, Husam Al-Amaireh, Tibor Cinkler

    Published 2025-01-01
    “…This paper introduces a comprehensive framework for reducing energy consumption in MEC environments by leveraging advanced optimization techniques and energy-efficient resource allocation algorithms. We propose a novel approach that dynamically adjusts the computational resources based on the current network load and the type of services requested, thus minimizing unnecessary energy consumption. …”
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  11. 211

    Research on Resource Allocation Method of Integrated Avionics System considering Fault Propagation Risk by Changxiao Zhao, Wei Zhang, Fangzheng Dong, Jun Dai, Lei Dong

    Published 2022-01-01
    “…The resource allocation method is evaluated according to the fault propagation risk model, and a heuristic algorithm is applied to optimize the resource allocation method of the IMA system. …”
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  12. 212

    Prediction and Optimization for Multi-Product Marketing Resource Allocation in Cross-Border E-Commerce by Yi Xie, Heng-Qing Ye, Wenbin Zhu

    Published 2025-06-01
    “…In cross-border e-commerce, effective marketing resource allocation is crucial due to the complexity introduced by diverse product categories, regional differences, and competition among category managers. …”
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  13. 213

    Game Theory Based Energy-Aware Uplink Resource Allocation in OFDMA Femtocell Networks by Jun Zhao, Wei Zheng, Xiangming Wen, Xiaoli Chu, Haijun Zhang, Zhaoming Lu

    Published 2014-03-01
    “…Simulation results show that the proposed algorithm can improve user utilities significantly, compared with existing power control and subchannel allocation algorithms.…”
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  14. 214

    Machine Learning in Biomedical Informatics: Optimizing Resource Allocation and Energy Efficiency in Public Hospitals by Agostino Marengo, Vito Santamato, Massimo Iacoviello

    Published 2025-01-01
    “…This paper presents a computational framework that combines supervised machine learning and multi-objective optimization to support data-driven decision-making for resource allocation in public healthcare systems. The study uses real-world data from 51 public hospitals across Southern and Northern Italy, ensuring a representative sample of diverse healthcare structures. …”
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  15. 215

    RL-MAB-Based Resource Allocation for Efficient Bandwidth Utilization in Industrial IoT Networks by Dongyeong Seo, Kidong Nam, Kwansoo Jung

    Published 2025-01-01
    “…The experimental performance evaluation shows that the proposed scheme improves network performance in terms of resource efficiency, scalability, energy efficiency, and mobility support compared to the typical resource allocation and scheduling schemes.…”
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  16. 216

    Energy-efficient device selection and resource allocation for edge-driven hierarchical federated learning by Yongwen Liu, Dongqing Liu, Lyes Khoukhi, Bo Wang, Lei Zhang, Yaoli Xu

    Published 2025-09-01
    “…However, existing frameworks often struggle with energy efficiency, adaptability to dynamic conditions, and the complex interplay between device selection and resource allocation. In this paper, we propose an energy-efficient hierarchical federated learning framework that jointly optimizes IoT device selection, local resource allocation, and base station resource allocation across a three-layer architecture. …”
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  17. 217

    Distributed RL-Based Resource Allocation and Task Offloading for Vehicular Edge of Things Computing by Ghada Afifi, Bassem Mokhtar

    Published 2025-01-01
    “…However, VEoTC frameworks face several challenges in effectively localizing and allocating the distributed resources and offloading tasks successfully due to the high mobility of vehicles and fluctuating user densities. …”
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  18. 218
  19. 219

    Research on the Capacity Allocation Optimization of Island Micro-grid Including Wind Power, Tidal Current Energy and Energy Storage by PANG Jiameng, ZANG Xiaodi

    Published 2022-12-01
    “…The three-objective optimization model uses the multi-objective particle swarm optimization algorithm to solve the established model, and obtains different capacity allocation schemes. …”
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  20. 220

    Decentralized and Joint Resource Allocation, Beamforming, and Beamcombining for 5G Networks With Heterogeneous MARL by Ala'a Al-Habashna, Jon Menard, Gabriel Wainer, Gary Boudreau

    Published 2025-01-01
    “…Our results show that the proposed paradigm can successfully optimize the task of joint resource allocation, beamforming, and combining. Furthermore, we provide a comparative analysis of the three different implementations, highlighting noteworthy insights into the strengths and limitations of fully distributed algorithms, such as IQL, in comparison to algorithms employing the Centralized Training with Decentralized Execution (CTDE) framework, exemplified by QTRAN and MADDPG.…”
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