Program Scheduling With Multi-Skill and External Resource Coordination Consideration Using Improved NSGA-II: Case Study by Heng Zhang, Jingbo Zhou, Huaying Ruan, Yixuan Qin

“…Technology-driven startups often experience fluctuations in business volume and their delivery peak exceeds the conventional functional department’s human resource staffing. Resource allocation is crucial for ensuring timely completion of project deliverables within resource constraints. …”
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New design paradigm for federated edge learning towards 6G:task-oriented resource management strategies by Zhiqin WANG, Jiamo JIANG, Peixi LIU, Xiaowen CAO, Yang LI, Kaifeng HAN, Ying DU, Guangxu ZHU

“…Methods: Using the federated learning network architecture, this paper analyzes the resource allocation and user scheduling schemes: 1. …”
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Short-term scheduling optimization of battery electric buses in the context of sustainable energy resources under uncertainty by Muhammad Ahmad Iqbal, Ismail I. Almaraj

“…The primary goal is to allocate BEB to the best CSs while focusing on increasing overall profit by serving the grid and passenger needs effectively. …”
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Routing algorithm for heterogeneous computing force requests based on computing first network by ZHANG Gang, LI Xi

“…The experiment verifies that algorithm has been optimized by an average of 8.85%, 15.51%, and 17.03% in terms of transmission success rate, convergence delay ratio, and load balancing compared to the IGAGCT algorithm and RBDQN algorithm, and 10.41%, 16.5%, and 16.81%, respectively from three aspects: heterogeneous request success rate, algorithms convergence delay rate, and load error rate of computing first networks.…”
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Comparative Performance Evaluation of Scheduling Algorithms using 5G‑Air‑Simulator by Moaath Saleh Abdulrahman, Buthaina Mosa Omran

“…With the spread of new applications, efficient scheduling algorithms are mandatory to handle the allocation of the limited spectrum resources to various types of traffic and to guarantee the requirements of the quality of service and the quality of experience informed by users. …”
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A New Multiobjective A∗ Algorithm With Time Window Applied to Large Airports by Bosheng Ba, Ye Yu, Ruixin Wang, Jean-Baptiste Gotteland, Yunqi Gao

“…This study proposes a multiobjective A∗ algorithm with time windows which takes into account the allocation of resources on airport taxiways and introduces factors such as turning angles, dynamic turning speeds, and dynamic characteristics of the ground operations. …”
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The Evaluation of Online Education Course Performance Using Decision Tree Mining Algorithm by Yongxian Yang

“…The decision tree mining algorithm can classify the data, grasp the teaching process of the teacher, and analyze the overall performance of the students, so as to realize the dynamic management of the educational administration and help the educational administration personnel to make the right decision, with more reasonable allocation of resources. …”
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Object Tracking Algorithm Based on Multi-Layer Feature Fusion and Semantic Enhancement by Jing Wang, Yanru Wang, Dan Yuan, Yuxiang Que, Weichao Huang, Yuan Wei

“…At the same time, in order to adapt to the changes in the surrounding environment of the object and establish good discrimination with similar objects, this paper proposes a dynamic mask strategy to optimize the attention allocation mechanism and finally employs an object template update mechanism to improve the adaptability of the model by comparing the spatio-temporal information of successive frames to update the object template in time, further enhancing its tracking performance in complex scenes. …”
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Adaptive Resource Optimization for IoT-Enabled Disaster-Resilient Non-Terrestrial Networks using Deep Reinforcement Learning by Fathe Jeribi, R. John Martin

“…Additionally, unmanned aerial vehicles (UAVs) are used to provide optimal coverage for IoT nodes in disaster areas, with coverage optimization achieved through the non-linear smooth optimization (NLSO) algorithm. Furthermore, we develop the multi-variable double deep reinforcement learning (MVD-DRL) framework for resource management, which addresses congestion and transmission power of IoT nodes to enhance network performance by maximize successful connections. …”
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Adaptive MCS selection and resource planning for energy-efficient communication in LTE-M based IoT sensing platform. by Nhu-Ngoc Dao, Minho Park, Joongheon Kim, Sungrae Cho

“…The proposed algorithm determines the optimal pair of MCS and the number of primary resource blocks (#PRBs), at which the transport block size is sufficient to packetize the sensing data within the minimum transmit power. …”
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Advancing Kidney Transplantation: A Machine Learning Approach to Enhance Donor–Recipient Matching by Nahed Alowidi, Razan Ali, Munera Sadaqah, Fatmah M. A. Naemi

“…(1) Background: Globally, the kidney donor shortage has made the allocation process critical for patients awaiting a kidney transplant. …”
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Multi-dimensional flux balance analysis to optimized resources and energy efficiency in MEC aided 5G networks by Rachit Patel, Rajeev Arya

“…In comparison to (1) Resource allocations using Q learning with considering parameter throughput-RA(QL-Munkres-TH), (2) Resource allocations using Q learning with considering parameter distance-RA(QL-Munkres-Dist), and (3) Resource allocation with considering maximum power-RA(Max-Power), the suggested method reduces energy consumption by 83.26%, 86.01%, and 88.34%, respectively. …”
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Algorithms to Identify Copied and Manipulated Spectrum Occupancy Data in Cognitive Radio Networks by Joseph Tolley, Carl B. Dietrich

“…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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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

“…First, for inbound processes, an algorithm-driven storage allocation model is proposed to solve stacker crane scheduling problems. …”
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Network media streaming offloading algorithm based on QoE in mobile edge network by Zaijian WANG, Hao CHENG

“…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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New Courteous Algorithm for Uplink Scheduling in LTE-Advanced and 5G Networks by Chafika Tata, Nassima Fellag, Michel Kadoch

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Parallel CUDA-Based Optimization of the Intersection Calculation Process in the Greiner–Hormann Algorithm by Jiwei Zuo, Junfu Fan, Kuan Li, Qingyun Liu, Yuke Zhou, Yi Zhang

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

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

“…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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Optimizing energy and latency in edge computing through a Boltzmann driven Bayesian framework for adaptive resource scheduling by Dinesh Sahu, Nidhi, Rajnish Chaturvedi, Shiv Prakash, Tiansheng Yang, Rajkumar Singh Rathore, Idrees Alsolbi

“…Abstract This paper presents a new approach based on Boltzmann Distribution and Bayesian Optimization to solve the energy-efficient resource allocation in edge computing. It employs Bayesian Optimization to optimize the parameters iteratively for the minimum energy consumption and latency. …”
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