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

“…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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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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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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DROVE: An Algorithm for Spatial and Temporal Disaggregation of On-road Vehicle Emission Inventories by Carlos M. González, Carlos D. Gómez, Beatriz H. Aristizábal

“…Hence, exercises for estimating atmospheric pollutant emissions are developed only in a macro-scale way, without allocating in space and time the emissions. In this study, we present a new computational algorithm named DROVE, for the disaggregation of on-road vehicle emissions in space and time. …”
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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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Enhancing IoT Connectivity through Advanced Scheduling at 142 GHz Sub-THz in 5G and Beyond Networks by Mohammed Mahfooudi, Ismail Angri, Mohammed Fattah, Moulhime EL Bekkali, Abdellah Najid

“…To ensure efficient optimization of the existing spectrum resources, the Radio Resource Management (RRM) function, responsible for managing and allocating radio resources like frequency, time, and power to ensure effective optimization of the existing spectrum, through an optimal scheduling algorithm can prioritize resource allocation based on specific requirements for IoT applications, such as latency, reliability, and throughput. …”
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AUV path planning method based on improved sparrow search algorithm by Lijun TANG, Yunxia FAN, Xingyu ZHOU, Qian SUN

“…Finally, the population size is dynamically updated using Thompson sampling, allowing the algorithm to adaptively allocate computational resources based on the complexity of the environment. …”
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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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Multi‐objective multi‐period optimal site and size of distributed generation along with network reconfiguration by Ghulam Abbas, Zhi Wu, Aamir Ali

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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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Optimal energy management for multi-energy microgrids using hybrid solutions to address renewable energy source uncertainty by M. Siva Ramkumar, Jaganathan Subramani, M. Sivaramkrishnan, Arunkumar Munimathan, Goh Kah Ong Michael, Mohammad Mukhtar Alam

“…Abstract Research in industrial grid energy management is essential due to increasing energy demands, rising costs, and the integration of renewable sources. Efficient energy management can reduce operational costs, enhance grid stability, and optimize resource allocation. …”
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Optimizing Rural Connectivity Through Hybrid Wireless-Wireline and Satellite Network Integration by Fareha Nizam, Teong Chee Chuah, Ying Loong Lee

“…In the user association scheme, the user association problem is formulated as a combinatorial optimization problem and solved using a greedy algorithm with a fairness-throughput trade-off that efficiently allocates resources based on network conditions and service priorities. …”
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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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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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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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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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