Showing 141 - 160 results of 1,377 for search '((( (resources OR sources) OR source) allocation algorithm ) OR ( sources allocation algorithm ))', query time: 0.29s Refine Results
  1. 141

    Task offloading and resource allocation in vehicle heterogeneous networks with MEC by Haibo ZHANG, Qiuji LUAN, Jiang ZHU, Fangwei LI

    Published 2018-09-01
    “…Based on the advantages of high-bandwidth and low-latency brought by mobile edge computing (MEC),which could provide IT service environment and cloud computing capability,combined with the long-term evolution unlicensed (LTE-U) technology,the task offloading decision and resource allocation issues in vehicle heterogeneous network were studied.Considering the link differentiation requirements,which were the high capacity of vehicle-to-roadside unit (V2I) links and the super reliability of vehicle-to-vehicle (V2V) links,quality of service (QoS) was modeled as the combination of capacity and latency.Firstly,the improved K-means algorithm was used to cluster the request vehicles according to different QoS to determine the communication mode.Secondly,the LTE-U technology based on non-competition period (CFP) which was combined with carrier aggregation (CA) technology,and the distribution Q-Learning algorithm were adopted to allocate the channel and power.The simulation results show that the proposed mechanism can maximize the V2I link traversal capacity while ensuring the reliability of the V2I link.…”
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  2. 142

    Joint communication and computing resource allocation in vehicular edge computing by Jianan Sun, Qing Gu, Tao Zheng, Ping Dong, Yajuan Qin

    Published 2019-03-01
    “…Then, we study the computation offloading decision problem in this system and propose a novel multi-objective vehicular edge computing task scheduling algorithm which jointly optimizes the allocation of communication and computing resources. …”
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  3. 143

    Robust Optimization for Integrated Construction Scheduling and Multiscale Resource Allocation by Qian Li, Sha Tao, Heap-Yih Chong, Zhijie Sasha Dong

    Published 2018-01-01
    “…This research investigates an integrated problem of construction scheduling and resource allocation. Inspired by complex construction practices, multi-time scale resources are considered for different length of terms, such as permanent staff and temporary workers. …”
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  4. 144

    Network slicing resource allocation strategy based on joint optimization by Zaijian WANG, Huimin GU

    Published 2023-05-01
    “…To improve network resource utilization that was decreased by different applications with different requirements in 5G networks, a network slicing resource allocation strategy based on joint optimization was proposed, which was utilized to maximize both network resource utilization and network revenue by comprehensively considering in tra-slice and inter-slice resource schedule.Firstly, the user’s average satisfaction function was defined in the inter-slicing resource allocation problem.Furthermore, in terms of the number of users, slicing schedule delay and priority, a proportional fair resource allocation algorithm based on quality of service (QoS) was proposed, which was employed to achieve the best tradeoff between fairness and the users’ requirements among slices.Secondly, after two functions (service degradation and resource migration) were introduced in the inter-slice resource schedule problem, two price models were established for internal access users and external access users respectively, where congestion and non-congestion conditions were analyzed.According to the proposed price models, a Stackelberg game between the base station and users was constructed, and a global search algorithm with low complexity was leveraged to obtain the best response of the game, where the best tradeoff between the base station revenue and user utility was obtained.Simulation results show that the proposed strategy can effectively improve resource utilization and network revenue while reducing network congestion.Therefore, it can better realize fairness in resource allocation.…”
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  5. 145

    Study on virtual resource allocation optimization in cloud computing environment by Li XU, Zhi-bin ZENG, Chuan YAO

    Published 2012-09-01
    “…Most existing researches of resource allocation in data center did not take into full consideration how to decrease energy consumption.The energy efficiency virtual resource allocation for cloud computing as a multi-objective optimization problem was formulated,which was then solved by intelligent optimization algorithm.The simulation results reveal that the strategy can successfully generate schedule scheme of different numbers of servers-VM with diverse characteristics and decrease the total operating energy of data center effectively.…”
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  6. 146

    The Task of Allocating Operations to Work Centers: Modern Approaches to Cost Minimization and Efficiency Improvement under Resource Constraints by Nikolay Nikitin, Igor Ilin, Alissa Dubgorn

    Published 2024-12-01
    “…Allocation of operations to work centers is a key management task in modern production systems. …”
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  7. 147

    Application of Optimization Algorithms in Voter Service Module Allocation by Edgar Jardón, Marcelo Romero, José-Raymundo Marcial-Romero

    Published 2025-06-01
    “…These findings align with principles of spatial justice and highlight the practical efficiency of heuristic-based solutions in administrative resource allocation. The main contribution of this study is the development and evaluation of a hybrid heuristic framework for allocating INE modules, demonstrating that combining multiple heuristics—with a genetic algorithm as the initial phase—significantly improves solution quality and computational efficiency.…”
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  8. 148

    Neural Network-Based Coordinated Virtual Inertia Allocation Method for Multi-Region Distribution Systems by Heng Liu, Jingtao Zhao, Zhi Wu, Shu Zheng

    Published 2025-06-01
    “…Following this, a genetic algorithm-based solving strategy is designed to achieve the global optimal allocation of virtual inertia. …”
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  9. 149
  10. 150

    Fast autoscaling algorithm for cost optimization of container clusters by José María López, Joaquín Entrialgo, Manuel García, Javier García, José Luis Díaz, Rubén Usamentiaga

    Published 2025-05-01
    “…In this paper we present FCMA (Fast Container to Machine Allocator), a resource allocation algorithm designed to calculate a suitable allocation of the resources of a cluster in autoscaling operations, to minimize cluster deployment costs. …”
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  11. 151

    RESEARCH ON APPLICABILITY OF BIONIC TECHNIQUES OF ARTIFICIAL BEE COLONIES FOR IMPLEMENTATION OF CLASSICAL TRANSPOSITION CIPHER CRYPTANALYSIS by Yury Olegovich Chernyshev, Alexander Sergeyevich Sergeyev, Engeny Olegovich Dybrov, Alexander Nikolaeyvich Ryazanov

    Published 2014-03-01
    “…It is shown that this is a subproblem of allocation, and it can b e solved with an artificial bee colony algorithm, as the bee behavior principle is a self - organization delivering a collective swarm goal. …”
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  12. 152

    Energy-Efficient Dual-Iteration Power Allocation for Two-Phase Relay System with Massive Antennas by Long Zhao, Wei Xiang, Jie Mei, Hui Zhao, Hang Long, Lin Li

    Published 2014-01-01
    “…Numerical results show that the proposed DIPA algorithms can greatly improve EE while guaranteeing spectrum efficiency (SE) when compared with the equal power allocation algorithm. …”
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  13. 153

    A heuristic mixed real-time task allocation of virtual utilization in multi-core processor by Hongbiao Liu, Mengfei Yang, Tingyu Wang, Chenghao Song, Shenghui Zhu, Xi Chen

    Published 2023-07-01
    “…Aiming at the task allocation problem when mixed real-time tasks are dynamically added, we propose a heuristic mixed real-time task allocation algorithm of virtual utilization VU-WF (Virtual Utilization Worst Fit) in multi-core processor. …”
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  14. 154

    Resource allocation strategy based on optimal matching auction in the enterprise network by Xin CONG, Lingling ZI, Xueli SHEN

    Published 2019-08-01
    “…To address the issue that the owners of computer are selfish in the enterprise networks,which caused the low available number of resource nodes and low efficiency of resource allocation,an optimized matching resource allocation strategy OMRA was proposed and its core was the auction mechanism.Selfishness was restrained and the number of available resources was increased by OMRA,so as the operating efficiency of the whole auction market was improved.First,the initial prices were determined by normalizing the costs of different type of resources on the beginning of auction.Secondly,an optimal matching auction algorithm was designed to maximize the interests of the auction markets.Then,service perfecting algorithm was performed such that the sellers could get more services at the current transaction value,thus ensuring the benefits of resource providers.At last,a request price updating algorithm was adopted to assurance that both sellers and buyers could get priorities in the next auction processing.Compared with the cloud resource allocating algorithm via fitness-enabled auction (CRAA/FA),the experiment results indicate that the efficiency of resource allocation improves by 10% and the benefits of market increase by 11.4%.…”
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  15. 155

    Flexible beam scheduling and resource allocation strategies for satellite Internet of things by LI Fulin, WANG Jingchao, DONG Yanjie, WANG Wei, MA Xiao

    Published 2025-03-01
    “…The beam scheduling algorithm based on separated swarm optimization (SSO-BSA) was proposed to solve the flexible beam pointing coordinates, and an on-demand resource allocation algorithm based on service value degree (ORAA-SVD) was designed to provide flexible resource allocation for beams and IoT terminals. …”
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  16. 156

    Adaptive resource allocation in multiuser OFDM system based on fairness threshold by ZHANG Chun-fa, ZHAO Xiao-hui

    Published 2011-01-01
    “…In traditional sub-carrier allocation process,user with the highest priority can choose best sub-carrier,which will result in low utilization of sub-carriers.Current improved algorithms can im-prove system capacity and reduce algorithm complexity by sacrificing certain fairness,but they may not achieve fairness requirement among users.In order to solve this problem,a new adaptive resource allo-cation algorithm based on fairness threshold was proposed,in which the priority of the sub-carrier allo-cation was determined by fairness threshold to achieve a rough tradeoff between capacity and fairness.Then power allocation base on particle swarm optimization(PSO) was introduced to realize the required fairness.Experimental results show that the proposed adaptive resource allocation algorithm can satisfy the fairness requirement threshold and improve system capacity.…”
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  17. 157

    Adaptive resource allocation in multiuser OFDM system based on fairness threshold by ZHANG Chun-fa, ZHAO Xiao-hui

    Published 2011-01-01
    “…In traditional sub-carrier allocation process,user with the highest priority can choose best sub-carrier,which will result in low utilization of sub-carriers.Current improved algorithms can im-prove system capacity and reduce algorithm complexity by sacrificing certain fairness,but they may not achieve fairness requirement among users.In order to solve this problem,a new adaptive resource allo-cation algorithm based on fairness threshold was proposed,in which the priority of the sub-carrier allo-cation was determined by fairness threshold to achieve a rough tradeoff between capacity and fairness.Then power allocation base on particle swarm optimization(PSO) was introduced to realize the required fairness.Experimental results show that the proposed adaptive resource allocation algorithm can satisfy the fairness requirement threshold and improve system capacity.…”
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  18. 158

    Resource allocation for multi-conductor power-cable carrier communications systems by XU Zhi-qiang1, ZHAI Ming-yue1, ZHAO Yu-ming2

    Published 2010-01-01
    “…Based on the measurements of cross-interfere coupling coefficient in a multi-conductor power cable, the characteristics of signal cross-interfere were analyzed. The mixed resource allocation model based on power-rate adaptation was introduced with the restrictions of power-line communications. …”
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  19. 159

    Optimal resource allocation for two-stage connectionless access with collision detection by Xin JIAN, Fang WANG, Jian SONG, Shu FU, Xiaoheng TAN, Xiaoping ZENG

    Published 2019-05-01
    “…Connectionless access allows massive machine type communication (mMTC) devices to transmit small packets without establishment of radio bearers,significantly reducing device power consumption and control signaling overhead.Two-stage connectionless access (TSCLA) improves throughput and resource efficiency by optimally allocating resources between scheduling request (SR) phase and data transmission phase,which can be used for bigger packets and high traffic load.Based on this,a comprehensive theoretical analysis of one kind of TSCLA with collision detection was conducted to investigate its performance limit and devise its optimal resource allocation scheme.In addition,to avoid the complexity of user number estimation,a dynamic resource allocation algorithm with feedback control was proposed.Numerical results are provided to validate the effectiveness of aforementioned theoretical results and show that comparing with the genie aided algorithm known exactly the number of users,the performance loss of the proposed algorithm is within 4%.These works together provide good references for appropriate resource dimensioning for mMTC related protocols.…”
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  20. 160

    Research on dynamic spectrum resource allocation in mobile base station networks by Ming-jie HE, Yong-jun XU, Feng WANG, Wei WU, Chao-nong XU

    Published 2014-11-01
    “…A priority policy of resource allocation for mobile base station networks was presented.In order to improve resource utilization and maintain good fairness,two resource allocation mechanisms based on graph theory were proposed.Finally,a distributed dynamic spectrum resource block allocation algorithm with low complexity was proposed.Simulation results show that the proposed algorithm has good performance.…”
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