Showing 681 - 700 results of 1,377 for search '((( resources OR resources) allocation algorithm ) OR ( (source OR sources) allocation algorithm ))', query time: 0.23s Refine Results
  1. 681

    Research on multi-UAV energy consumption optimization algorithm for cellular-connected network by Jingming XIA, Yufeng LIU, Ling TAN

    Published 2023-02-01
    “…In complex time-varying environment, the ground base station (GBS) may not assist the UAV.Therefore, a mobile edge computing (MEC) cellular-connected network based on digital twin (DT) technology was studied.Given the efficiency of multi-UAV, multiple high-altitude balloon (HAB) equipped with MEC servers were introduced.On this basis, an energy minimization problem for all UAV was proposed, and a multi-UAV trajectory optimization and resource allocation scheme was presented to solve it.The double deep Q-network (DDQN) was applied to handle the association between multi-UAV and multi-HAB, and the multi-UAV trajectory and computing resource allocation were jointly optimized by the successive convex approximation (SCA) and the block coordinate descent (BCD).Simulation experiments verify the feasibility and effectiveness of the proposed algorithm.The system energy consumption is reduced by 30%, better than the comparison algorithms.…”
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  2. 682

    Reducing hydrogen consumption in hybrid electric vehicles using aquila optimization algorithm by A.M. Nassef, H.E. Ghadbane, E.T. Sayed, H. Rezk

    Published 2025-04-01
    “…Implementing an energy management strategy to enhance the performance of fuel cell electric vehicles by optimizing the allocation of power among different energy sources is a crucial engineering problem. …”
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  3. 683

    QoS Aware Task Scheduling Using Hybrid Genetic Algorithm in Cloud Computing by Keyvan Atbaee Tabary, Homayun Motameni, Behnam Barzegar, Ebrahim Akbari, Hossien Shirgahi, Mehran Mokhtari

    Published 2025-01-01
    “…PSO-SMPIA and GA-SMPIA algorithms are presented for task scheduling and resource allocation with the aim of reducing makespan and total execution time, and increasing resource utilization in CC. …”
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  4. 684

    Service chain deployment algorithms for deterministic end-to-end delay upper bound by Ze’nan WANG, Jiao ZHANG, Shuo WANG, Tao HUANG, F.Richard Yu

    Published 2021-11-01
    “…To solve the problem that the current service chain deployment algorithms cannot guarantee the delay of each packet passing through the service chain (SC), a SC deployment algorithm for deterministic end-to-end delay upper bound was proposed.First, the end-to-end delay bound of the SC was derived based on network calculus.Then, the deterministic end-to-end delay bound of the SC was achieved by collaboratively optimizing the routing of SC and the resource allocation of the virtual network function nodes in the SC.The experimental results show that the proposed algorithm can effectively improve the volume of accepted SC while guaranteeing that the end-to-end delay of each packet satisfies the delay requirements.…”
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  5. 685

    Fair and efficient opportunistic interference alignment algorithm based on round-robin scheduling by Xian-zhong XIE, Hua-bing LU, Zhao-yuan SHI

    Published 2017-10-01
    “…Opportunistic interference alignment (OIA) algorithm was proposed for the practical implementation of interference alignment (IA).A fair and efficient OIA algorithm was presented for the unfairness in resource allocation and high dependence of tremendous users in the existing OIA algorithms.Firstly,the users with the best channel was selected in the primary cell based on round-robin scheduling after the coordinate cluster was determined.Then,the interference from the primary users was eliminated by skillfully designing the useful signal spaces in the subordinate cells.Furthermore,the users with the minimum interference leakage was selected in the subordinate cells.Finally,the fairness performance was theoretically analyzed.Simulation results show that both the sum-rate and fairness of the proposed algorithm are significantly higher than that of the conventional algorithm with less interference leakage.Besides,the users can achieve a quick access.…”
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  6. 686

    Clustering of High School Students Academic Scores Using K-Means Algorithm by Chairunisa Azzahra, Sriani Sriani

    Published 2025-03-01
    “…Additionally, clustering outcomes provide valuable insights for refining teaching strategies, allocating resources more effectively, and personalizing learning approaches to suit each student's needs. …”
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  7. 687
  8. 688

    Routing algorithm for heterogeneous computing force requests based on computing first network by ZHANG Gang, LI Xi

    Published 2025-02-01
    “…Due to the particularity and uniqueness of computing force requests, how to find an effective path set with non-intersecting transmission links for a group of heterogeneous computing force requests, so that the group of requests can reach their respective destination computing force nodes, and thus allocate computing force resources for the group of requests, is a key issue facing current computing first networks. …”
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  9. 689

    Algorithms to Identify Copied and Manipulated Spectrum Occupancy Data in Cognitive Radio Networks by Joseph Tolley, Carl B. Dietrich

    Published 2025-01-01
    “…Spectrum Access Systems (SASs) and similar systems coordinate access to shared radio frequency bands to efficiently allocate the use of spectrum between users in a locality. …”
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  10. 690

    Joint beam hopping and coverage control optimization algorithm for multibeam satellite system by Guoliang XU, Feng TAN, Yongyi RAN, Feng CHEN

    Published 2023-04-01
    “…To improve the performance of multibeam satellite (MBS) systems, a deep reinforcement learning-based algorithm to jointly optimize the beam hopping and coverage control (BHCC) algorithm for MBS was proposed.Firstly, the resource allocation problem in MBS was transformed to a multi-objective optimization problem with the objective maximizing the system throughput and minimizing the packet loss rate of the MBS.Secondly, the MBS environment was characterized as a multi-dimensional matrix, and the objective problem was modelled as a Markov decision process considering stochastic communication requirements.Finally, the objective problem was solved by combining the powerful feature extraction and learning capabilities of deep reinforcement learning.In addition, a single-intelligence polling multiplexing mechanism was proposed to reduce the search space and convergence difficulty and accelerate the training of BHCC.Compared with the genetic algorithm, the simulation results show that BHCC improves the throughput of MBS and reduces the packet loss rate of the system, greedy algorithm, and random algorithm.Besides, BHCC performs better in different communication scenarios compared with a deep reinforcement learning algorithm, which do not consider the adaptive beam coverage.…”
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  11. 691

    Economic operation analysis of the power grid combining communication network and distributed optimization algorithm by Yi Zhifei

    Published 2025-05-01
    “…It is necessary to strengthen communication and resource allocation in practical applications.…”
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  12. 692

    An energy saving clustering algorithm based on artificial bee colony in ultra dense network by Pengguang ZHOU, Junwei HUANG, Renchi ZHANG, Hao XU

    Published 2017-02-01
    “…In ultra dense network (UDN),the dense deployment of low power base station (BS) will increase the system's energy consumption and cause the waste of the scarce spectrum resources.Aiming to explore the feasible method of energy saving system and interference coordination,BS sleeping-waking-active mechanism in UDN was proposed,which would reduce the opening time of the sleeping BS.Also an adjusted artificial bee colony algorithm was proposed which used the least colors to dye the BS in topology,then power allocation of active BS in different cluster was optimized.Simulations show that the sleeping-waking-active mechanism can improve the energy efficiency of the system,and the clustering algorithm can promote the spectrum efficiency and throughput.…”
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  13. 693

    An innovative genetic algorithm-based master schedule to optimize job shop scheduling problem by Thi Phuong Quyen Nguyen, Thi Hoa Thuong Le

    Published 2024-12-01
    “…In this scenario, production scheduling has arisen as an essential function that contributes to the effective allocation of organizational resources in the production process, while shortening production time and satisfying customer deadlines. …”
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  14. 694

    Storage Location Assignment in Emergency Reserve Warehouses: A Multi-Objective Optimization Algorithm by Chen Liang, Tao Cui, Yu Wei, Kun Zhao, Xiongping Yue, Chao Wang

    Published 2025-05-01
    “…The efficiency of emergency response operations is critically dependent on the strategic storage and allocation of emergency supplies. Proper management of these resources reduces economic impacts and ensures prompt availability in crises. …”
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  15. 695

    Efficient task scheduling for cloud computing: a comparative survey of state-of-the-art algorithms by Aziza Algarni

    Published 2023-06-01
    “…Multiple independent tasks need to be handled by cloud computing, and static and dynamic scheduling plays a crucial role in allocating tasks to the right resources. This is especially important in heterogeneous environments, where algorithms can improve load balancing and enhance cloud computing's efficiency. …”
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  16. 696

    An Integrated Implementation Framework for Warehouse 4.0 Based on Inbound and Outbound Operations by Jizhuang Hui, Shaowei Zhi, Weichen Liu, Changhao Chu, Fuqiang Zhang

    Published 2025-07-01
    “…First, for inbound processes, an algorithm-driven storage allocation model is proposed to solve stacker crane scheduling problems. …”
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  17. 697

    A GD-PSO Algorithm for Smart Transportation Supply Chain ABS Portfolio Optimization by Yingjia Sun, Hongfeng Ren

    Published 2021-01-01
    “…In this article, a penalty function based on graph density (GD) was introduced to the particle swarm optimization algorithm (PSO), and a GD-PSO algorithm was proposed. …”
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  18. 698

    Gradual Optimization of University Course Scheduling Problem Using Genetic Algorithm and Dynamic Programming by Xu Han, Dian Wang

    Published 2025-03-01
    “…Additionally, by incorporating a greedy algorithm for classroom allocation, the utilization of classroom resources was further enhanced. …”
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  19. 699

    Network media streaming offloading algorithm based on QoE in mobile edge network by Zaijian WANG, Hao CHENG

    Published 2024-02-01
    “…Aiming at the problems of high-latency, high energy consumption, high bandwidth, and poor quality of experience (QoE) caused by emerging network media streaming business in mobile edge computing, a computing offloading algorithm based on QoE feedback configuration was proposed.Firstly, both preprocessing and priority were comprehensively considered to maximize network resource utilization.Meanwhile, different weights were assigned to the computation tasks for establishing a resource allocation relationship.Secondly, after comprehensively taking into account deadline, computing resource, power and bandwidth constraint, an QoE model was established where the optimization objective was the weighted sum of task delay, energy consumption and precision, and the method of Lagrange multipliers was utilized to solve the established model.Simulation results indicate that, compared with the deep reinforcement learning-based online offloading algorithm, the proposed algorithm can effectively optimize the resource allocation and better improve the QoE.…”
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  20. 700

    Network media streaming offloading algorithm based on QoE in mobile edge network by Zaijian WANG, Hao CHENG

    Published 2024-02-01
    “…Aiming at the problems of high-latency, high energy consumption, high bandwidth, and poor quality of experience (QoE) caused by emerging network media streaming business in mobile edge computing, a computing offloading algorithm based on QoE feedback configuration was proposed.Firstly, both preprocessing and priority were comprehensively considered to maximize network resource utilization.Meanwhile, different weights were assigned to the computation tasks for establishing a resource allocation relationship.Secondly, after comprehensively taking into account deadline, computing resource, power and bandwidth constraint, an QoE model was established where the optimization objective was the weighted sum of task delay, energy consumption and precision, and the method of Lagrange multipliers was utilized to solve the established model.Simulation results indicate that, compared with the deep reinforcement learning-based online offloading algorithm, the proposed algorithm can effectively optimize the resource allocation and better improve the QoE.…”
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