Showing 641 - 660 results of 1,377 for search '((( (resource OR source) OR sourcesss) allocation algorithm ) OR ( sources allocation algorithm ))', query time: 0.34s Refine Results
  1. 641
  2. 642

    A node deployment and resource optimization method for CPDS based on cloud‐fog‐edge collaboration by Xiaoping Xiong, Geng Yang

    Published 2024-11-01
    “…Subsequently, an improved multi‐objective particle swarm optimization algorithm (MWM‐MOPSO) is employed to solve the task resource allocation problem. …”
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    Article
  3. 643

    Multiple UAV Swarms Collaborative Firefighting Strategy Considering Forest Fire Spread and Resource Constraints by Pei Zhu, Rui Song, Jiangao Zhang, Ziheng Xu, Yaqi Gou, Zhi Sun, Quan Shao

    Published 2024-12-01
    “…To address the demands of efficient forest fire detection and suppression, an adaptive multiple UAV swarm collaborative firefighting strategy considering dynamic forest fire spread and resource constraints was proposed in this paper. The multiple UAV swarm adaptive information-driven collaborative search (MUSAIDCS) algorithm and the resource-limited firefighting model were established. …”
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    Article
  4. 644

    A Multiconstrained Grid Scheduling Algorithm with Load Balancing and Fault Tolerance by P. Keerthika, P. Suresh

    Published 2015-01-01
    “…A scheduling algorithm is said to be efficient if and only if it performs better resource allocation even in case of resource failure. …”
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    Article
  5. 645

    Human resource management model based on multi-objective differential evolution and multi-skill scheduling by Yanxia Dong, Tiantian Lu

    Published 2025-12-01
    “…This provides a scientific basis for enterprises to allocate human resources reasonably and improve project efficiency. …”
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    Article
  6. 646

    A Novel NSGA-III-GKM++ Framework for Multi-Objective Cloud Resource Brokerage Optimization by Ahmed Yosreddin Samti, Ines Ben Jaafar, Issam Nouaouri, Patrick Hirsch

    Published 2025-06-01
    “…Cloud resource brokerage is a fundamental challenge in cloud computing, requiring the efficient selection and allocation of services from multiple providers to optimize performance, sustainability, and cost-effectiveness. …”
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    Article
  7. 647

    Application of improved clustering algorithm in mixed teaching of modern educational technology by Lei Shu, Guirong Li

    Published 2025-08-01
    “…The improved clustering algorithm demonstrates high precision and flexibility, enabling accurate resource allocation, effective teaching content, and targeted pacing adjustments based on students’ learning progress. …”
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    Article
  8. 648
  9. 649

    Intelligent Integration Method of AI English Teaching Resource Information under Multi-Agent Collaboration by Minjuan Liu

    Published 2022-01-01
    “…Moreover, this article analyzes the principles and properties of the three algorithms, ALO, GWO, and MFO, and integrates them into the D2D power allocation problem in the two communication modes. …”
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    Article
  10. 650

    Carbon Dioxide Storage Site Location and Transport Assignment Optimization for Sustainable Maritime Transport by Yanmeng Tao, Ying Yang, Yuquan Du, Shuaian Wang

    Published 2025-05-01
    “…Maritime carbon dioxide (CO<sub>2</sub>) transport plays a pivotal role in facilitating carbon capture and storage (CCS) systems by connecting emission sources with appropriate storage sites. This process often incurs significant transportation costs, which must be carefully balanced against penalties for untransported CO<sub>2</sub> resulting from cost-driven decisions. …”
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    Article
  11. 651

    An Improved Coral Reef Optimization-Based Scheduling Algorithm for Cloud Computing by Shuzhen Wan, Lixin Qi

    Published 2021-01-01
    “…In this paper, we establish a resource allocation framework and propose a novel task scheduling algorithm. …”
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    Article
  12. 652

    Research on the security of national secret algorithm based compute first networking by Jie PAN, Lan YE, Pengfei ZHANG, Zhonggui BU

    Published 2023-08-01
    “…With the promotion of national secret algorithm, in-depth research on the arithmetic network was carried out, a more efficient and reasonable security scheme for the arithmetic network was proposed, ensuring the data security and privacy of the arithmetic network with the help of the state secret algorithm.The main elements of the design program included: Supporting arithmetic demand and cryptographic invocation through the underlying resources, the arithmetic orchestration layer provided the ability to orchestrate data arithmetic, meanwhile, the arithmetic scheduling layer intelligently discerned the optimal nodes for arithmetic resource scheduling and allocation; the cryptographic reinforcement layer used the national secret algorithm based on hardware support with the help of public key cryptosystem, hash function, digital envelope, homomorphic encryption, blockchain and other technologies.Focusing on arithmetic network access security, transmission security, data security and privacy protection aspects of security implementation.An architecture and application form was innovatively proposed to guarantee the data security of the arithmetic network, which could meet the needs of the application layer arithmetic in the scenarios of big data, intelligent technology, etc..The security of the arithmetic network is enhanced by empowering the arithmetic network through the state-secret algorithm.…”
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  13. 653

    Mission Planning for LEO Satellite IoT Constellation Based on Genetic Algorithm by Yanhong LI, Qiang LYU, Junmin LIANG, Shigang FENG, Junhou MIAO

    Published 2024-06-01
    “…A mission planning algorithm based on genetic algorithm was designed for LEO satellite IoT constellation with no inter-satellite links, aimed to achieve real-time data communication through multiple ground stations while maximized the resource allocation of satellites and ground stations.Firstly, the objective function to maximized the service duration of satellites in orbit and the constraints on clashed tasks were designed, constructed the mission planning model for LEO satellite IoT constellation.Then, based on genetic algorithm, clashed tasks and early stopping mechanism were introduced, and the mission planning algorithm for the LEO satellite IoT constellation was designed.On this basis, experiments were conducted use a constellation of 18 LEO communication satellites without inter-satellite links and 4 ground stations.In addition, in order to verified the performance of the algorithm, first come first service (FCFS) algorithm was also used for mission planning of the experimental data.The experiments compared with FCFS showed that the designed mission planning algorithm for LEO satellite IoT constellation could significantly improve the scheduling capacity of ground stations for receiving data of communication satellites, addressed the contradiction of insufficient ground stations with a large number of satellites.…”
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  14. 654

    Modeling and Optimization of Cable Production Scheduling by Incorporating an Ant Colony Algorithm by Changbiao Zhu, Chongxin Wang, Zhonghua Ni, Xiaojun Liu, Abbas Raza

    Published 2025-04-01
    “…This work proposed a cable production scheduling optimization method based on an ant colony algorithm, aiming at solving the problems of the inefficiency and underutilization of resources in the process of traditional cable scheduling. …”
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  15. 655
  16. 656

    Novel cooperative power control game algorithm for cognitive radio systems by CHENG Shi-lun1, YANG Zhen1, ZHANG Hui2

    Published 2007-01-01
    “…In order to fair optimally allocate the limited cognitive radio resource,a cognitive radio system was developed based on STBC OFDM-CDMA network systems and a novel Nash bargaining solution named NBS of cooperative power control was adopted in this system,the transmitted power was dynamically adapted based on channel conditions,maxi-mal network throughput and power limits.Simulation results show that the novel algorithm can regulate their transmitter powers,fair optimally allocate radio resource.At the same power consumption,the network throughput is thereby im-proved obviously.…”
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    Article
  17. 657

    Novel cooperative power control game algorithm for cognitive radio systems by CHENG Shi-lun1, YANG Zhen1, ZHANG Hui2

    Published 2007-01-01
    “…In order to fair optimally allocate the limited cognitive radio resource,a cognitive radio system was developed based on STBC OFDM-CDMA network systems and a novel Nash bargaining solution named NBS of cooperative power control was adopted in this system,the transmitted power was dynamically adapted based on channel conditions,maxi-mal network throughput and power limits.Simulation results show that the novel algorithm can regulate their transmitter powers,fair optimally allocate radio resource.At the same power consumption,the network throughput is thereby im-proved obviously.…”
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    Article
  18. 658

    Dual-Resource Optimization Configuration and Collaborative Scheduling for Flexible Job Shop Under Worker Flexibility Constraints by Zijie Ren, Hongyi Qu, Mejdl Safran, Jiafu Wan

    Published 2025-01-01
    “…This paper focuses on achieving resource allocation via personnel flexibility quantification and dual-resource collaborative scheduling optimization. …”
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    Article
  19. 659

    A Novel UCAN Power Control Algorithm Based on the Stackelberg Game by Huaping Chen, Zhiyu Wang, Zhongyang He, Guoqiang Li

    Published 2024-01-01
    “…In this paper, A novel UnderWater Cognitive Acoustic Sensor Network(UCANs) power control algorithm based on the Stackelberg game is proposed to solve the problems of low system capacity, high inter-node interference, and poor communication quality due to unreasonable power allocation when Under Water Acoustic Sensor Networks (UASNs) share spectrum resources. …”
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    Article
  20. 660

    Improved salp swarm algorithm based optimization of mobile task offloading by Aishwarya R., Mathivanan G.

    Published 2025-05-01
    “…Results This technique harnesses the optimization capabilities of the improved salp swarm algorithm (ISSA) to intelligently allocate computing tasks between mobile devices and the cloud, aiming to concurrently minimize energy consumption, and memory usage, and reduce task completion delays. …”
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