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

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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

“…The dynamic nature of NTNs makes static resource allocation insufficient, necessitating adaptive strategies to address varying demands and environmental conditions during disaster management. …”
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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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Routing algorithm for heterogeneous computing force requests based on computing first network by ZHANG Gang, LI Xi

“…Due to the particularity and uniqueness of computing force requests, how to find an effective path set with non-intersecting transmission links for a group of heterogeneous computing force requests, so that the group of requests can reach their respective destination computing force nodes, and thus allocate computing force resources for the group of requests, is a key issue facing current computing first networks. …”
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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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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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EdgeGuard: Decentralized Medical Resource Orchestration via Blockchain-Secured Federated Learning in IoMT Networks by Sakshi Patni, Joohyung Lee

“…EdgeGuard uses edge computing to improve system scalability and efficiency by offloading computational tasks from IoMT devices with limited resources. We have made several technological advances, including a lightweight blockchain consensus mechanism designed for IoMT networks, an adaptive edge resource allocation method based on reinforcement learning, and a federated learning algorithm optimized for medical data with differential privacy. …”
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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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Economic operation analysis of the power grid combining communication network and distributed optimization algorithm by Yi Zhifei

“…It is necessary to strengthen communication and resource allocation in practical applications.…”
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A GD-PSO Algorithm for Smart Transportation Supply Chain ABS Portfolio Optimization by Yingjia Sun, Hongfeng Ren

“…In this article, a penalty function based on graph density (GD) was introduced to the particle swarm optimization algorithm (PSO), and a GD-PSO algorithm was proposed. …”
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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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An energy saving clustering algorithm based on artificial bee colony in ultra dense network by Pengguang ZHOU, Junwei HUANG, Renchi ZHANG, Hao XU

“…In ultra dense network (UDN),the dense deployment of low power base station (BS) will increase the system's energy consumption and cause the waste of the scarce spectrum resources.Aiming to explore the feasible method of energy saving system and interference coordination,BS sleeping-waking-active mechanism in UDN was proposed,which would reduce the opening time of the sleeping BS.Also an adjusted artificial bee colony algorithm was proposed which used the least colors to dye the BS in topology,then power allocation of active BS in different cluster was optimized.Simulations show that the sleeping-waking-active mechanism can improve the energy efficiency of the system,and the clustering algorithm can promote the spectrum efficiency and throughput.…”
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An innovative genetic algorithm-based master schedule to optimize job shop scheduling problem by Thi Phuong Quyen Nguyen, Thi Hoa Thuong Le

“…In this scenario, production scheduling has arisen as an essential function that contributes to the effective allocation of organizational resources in the production process, while shortening production time and satisfying customer deadlines. …”
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Storage Location Assignment in Emergency Reserve Warehouses: A Multi-Objective Optimization Algorithm by Chen Liang, Tao Cui, Yu Wei, Kun Zhao, Xiongping Yue, Chao Wang

“…The efficiency of emergency response operations is critically dependent on the strategic storage and allocation of emergency supplies. Proper management of these resources reduces economic impacts and ensures prompt availability in crises. …”
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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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Enhancing Uplink Communication in Wireless Powered Communication Networks Through Rate-Splitting Multiple Access and Joint Resource Optimization by Iqra Hameed, Mario R. Camana, Mohammad Abrar Shakil Sejan, Hyoung Kyu Song

“…However, their performance is often limited by interference in uplink communication and inefficient resource allocation. To address these challenges, we propose an RSMA-aided WPCN framework, which optimizes rate-splitting factors, power allocation, and time division to enhance spectral efficiency and user fairness. …”
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Gradual Optimization of University Course Scheduling Problem Using Genetic Algorithm and Dynamic Programming by Xu Han, Dian Wang

“…Additionally, by incorporating a greedy algorithm for classroom allocation, the utilization of classroom resources was further enhanced. …”
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Research on E-Commerce Inventory Sales Forecasting Model Based on ARIMA and LSTM Algorithm by Chenyang Wang, Junsheng Wang

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