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

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

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

“…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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A multi-greedy spectrum auction algorithm for cognitive small cell networks by Feng Zhao, Bo Liu, Hongbin Chen

“…The proposed algorithm can achieve conflict-free spectrum allocations that maximize the utility and spectrum allocation efficiency. …”
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Optimizing music course scheduling with real number encoding and chaos genetic algorithm by Shu Li

“…Traditional scheduling systems usually use simple algorithms or manual intervention, resulting in low efficiency and uneven resource allocation. …”
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Research on energy-efficient physical-layer secure transmission mechanism in decode-and-forward cooperative networks by Dong WANG, Yong-cheng LI, Bo BAI, Man-xi WANG

“…The maximization problem of secure energy efficiency (EE) in decode-and-forward relay networks was investigated considering the power and energy constraints in physical-layer secure transmission.An iterative algorithm for power allocation was proposed based on fractional programming and DC (difference of convex functions) programming.This algorithm jointly allocated power for source and relay nodes to achieve energy-efficient secure transmission,subject to the peak power constraint of each node and the minimum secrecy rate requirement of the system.Simulation results demonstrate that the propose algorithm can improve the secure EE significantly compared with the conventional secrecy rate maximization strategy.…”
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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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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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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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Research on multi-UAV energy consumption optimization algorithm for cellular-connected network by Jingming XIA, Yufeng LIU, Ling TAN

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

“…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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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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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

“…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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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

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

“…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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Innovative application of particle swarm algorithm in the improvement of digital enterprise management efficiency by Shengnan Zhang

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

“…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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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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