QoS-Based Resource Allocation in Multicarrier NOMA-IBFD Cellular System With Sectorization by Ananda Kumar Karem, A. Krishna Chaitanya, Satya Kumar Vankayala, Seungil Yoon, Ganesh Chandrasekaran, Karthik Muralidhar

“…Subsequently, we extend our investigation at sector level to obtain a comprehensive understanding of network dynamics within a more confined coverage area. We use orthogonal resource allocation and half duplex scenarios as benchmarks to evaluate the performance of proposed algorithm. …”
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Energy-Efficient UAV Relaying Robust Resource Allocation in Uncertain Adversarial Networks by Shakil Ahmed, Mostafa Zaman Chowdhury, Saifur Rahman Sabuj, Md Imtiajul Alam, Yeong Min Jang

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Evaluating the Efficiency of Gray Wolf Optimization and Colonial Competition Algorithm in Load Balancing of Distributed Systems by Asghar Molaei-Yeznabad, Amirhossein Dehghani

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Utility-driven based co-allocation resource reservation strategy in computational grid by Chang-song DING, Zhi-ying WANG, Zhi-gang HU

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Deep and robust resource allocation for random access network based with imperfect CSI by Weihua WU, Guanhua CHAI, Qinghai YANG, Runzi LIU

“…A deep and robust resource allocation framework was proposed for the random access based wireless networks,where both the communication channel state information (C-CSI) and the interference channel state information (I-CSI) were uncertain.The proposed resource allocation framework considered the optimization objective of wireless networks as a learning problem and employs deep neural network (DNN) to approximate optimal resource allocation policy through unsupervised manner.By modeling the uncertainties of CSI as ellipsoid sets,two concatenated DNN units were proposed,where the first was uncertain CSI processing unit and the second was the power control unit.Then,an alternating iterative training algorithm was developed to jointly train the two concatenated DNN units.Finally,the simulations verify the effectiveness of the proposed robust leaning approach over the nonrobust one.…”
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A cooperative multicast efficient resource allocation scheme based on limited feedback by Lei CHEN

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LEO satellite Internet resource allocation strategy based on terminal traffic prediction by SHEN Fei, LYU Chengcheng, ZHANG Jiaxuan, RUAN Xiaoting

“…A resource allocation strategy for the low earth orbit (LEO) satellite Internet based on terminal traffic prediction was proposed to address the problems of blind coverage spots in ground network and the low resource utilization of satellite network. …”
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A Computational Offloading Method for Edge Server Computing and Resource Allocation Management by Muna Al-Razgan, Taha Alfakih, Mohammad Mehedi Hassan

“…Furthermore, we propose availability of a virtual machine resource algorithm (AVM) based on the availability of VM in edge cloud servers for efficient resource allocation and task scheduling. …”
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Jumping knowledge graph attention network for resource allocation in wireless cellular system by Qiushi Sun, Zhou Fang, Yin Li, Ovanes Petrosian

“…The realization of these features hinges on the development of rational resource allocation strategies to optimize the utilization of radio resources. …”
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Remote Embedded System for Agricultural Field Monitoring: Enhancing Resource Allocation in Agriculture by Ronald J. Contijo, Lucas C. de Camargo, Renan O. A. Takeuchi, André L. S. Moscato, Lafaiete H. R. Leme, Wenderson N. Lopes

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MATHEMATICAL MODEL OF RESOURCE DISTRIBUTION OF THE COMPUTING CLUSTER OF CLOUD DATA CENTERS by V. P. Mochalov, G. I. Linets, N. Y. Bratchenko, I. S. Palkanov

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Resource Allocation in STAR-RIS-Aided SWIPT With RSMA via Meta-Learning by Mojtaba Amiri, Elaheh Vaezpour, Sepideh Javadi, Mohammad Robat Mili, Mehdi Bennis, Eduard Axel Jorswieck

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Resource allocation for coexistence of eMBB and bursty URLLC based on queueing with preemption by Wei Guo, Kai Liang, Yuewen Song, Xiaoli Chu, Gan Zheng, Kai-Kit Wong

“…In this paper, we propose a method to allocate computing and radio resources for coexisting eMBB and bursty URLLC services by preempting both computing queues in the base station (BS) and time-frequency resources at the air interface. …”
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SHERA: SHAP-Enhanced Resource Allocation for VM Scheduling and Efficient Cloud Computing by Ashwin Singh Slathia, Abhiram Sharma, P. B. Krishna, Saksham Anand, Ayush Rathi, Linda Joseph, Xiao-Zhi Gao

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A Semi-Distributed Scheme for Mode Selection and Resource Allocation in Device-to-Device-Enabled Cellular Networks Using Matching Game and Reinforcement Learning by Ibrahim Sami Attar, Nor Muzlifah Mahyuddin, M. H. D. Nour Hindia

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Measuring Outcomes in Healthcare Economics using Artificial Intelligence: with Application to Resource Allocation by Feras A. Batarseh, Chih-Hao Huang

“…This manuscript presents three intelligent methods that provide data-driven indicators to help healthcare managers organize their economics and identify the most optimum plan for resource allocation and sharing. Using reinforcement learning, genetic algorithms, traveling salesman, and clustering, we experimented with different healthcare variables and presented tools and outcomes that could be applied at health institutes. …”
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QoS guaranteed multi-user and multi-traffic scheduling algorithm for IEEE 802.16 network by BAI Bo1, CAO Zhi-gang1, CHEN Wei1, I Chih-lin2

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MULTIPLE-PURPOSE SOLUTION TO HOMOGENEOUS ALLOCATION PROBLEMS BASED ON MODIFIED ROMANOVSKY ALGORITHM AND SELECTIVE-PERMUTATION ALGORITHM by Rudolf A. Neydorf, Artem A. Zhikulin

“…The problem on improving precision properties of the fast approx imate algorithms without sacrifice of their resource properties is set. …”
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Spectrum allocation algorithm of elastic optical networks in power distribution system by Biyou ZHAO, Shanhui ZHANG, Jinshuai WANG

“…In order to effectively improve the resource utilization of information transmission network in reality,the spectrum allocation problem in flexible optical network in smart grid environment was analyzed,and a spectrum allocation method was proposed.Combining the advantages of genetic algorithm and ant colony algorithm,the genetic algorithm was used to generate the initial solution.Finally,the optimal solution of the spectrum allocation problem was obtained by the characteristics of positive feedback of ant colony algorithm and efficient convergence.The performance of the optimization algorithm mentioned was verified by software simulation.The proposed algorithm can optimize the use of idle spectrum resources to meet the needs of mass data transmission in distribution network,and improve the reliability of distribution network communication system,which is of great significance to the safe and reliable operation of smart grid.…”
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Adaptive bandwidth allocation algorithm based on the multi-threshold reservation mechanism by Geng CHEN, Wei-wei XIA, Lian-feng SHEN

“…An adaptive bandwidth allocation algorithm based on multi-threshold reservation mechanism is proposed to guarantee the quality of service (QoS) of multi-services in heterogeneous wireless networks.With the bandwidth reserva-tion mechanism by setting multi-threshold in each network for every traffic,the adaptive bandwidth allocation scheme according to the transmission rate levels requirements for traffic k and the network status can be formulated as an optimal problem with the constraints of the bandwidth allocation matrix for each traffic and all users based on the multi-homing technology.A procedure of the iterative method is presented to solve the optimal problem of the formulated adaptive bandwidth allocation scheme.The optimized bandwidth allocation matrixes for traffics and for all users are obtained for the real-time network throughput maximization under bandwidth reserving thresholds and network capacity constrains and the bandwidth resource utilization efficiency of heterogeneous wireless network can be increased.Numerical simula-tion results show that the proposed algorithm can support QoS requiring transmission rate grades,decrease the new call blocking probability,increase the average user access rate and improve the network throughput of the heterogeneous wireless network by 40% to the largest extent.…”
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