Adaptive Real-Time Transmission in Large-Scale Satellite Networks Through Software-Defined-Networking-Based Domain Clustering and Random Linear Network Coding by Shangpeng Wang, Chenyuan Zhang, Yuchen Wu, Limin Liu, Jun Long

“…Experimental results indicate that the proposed method reduced resource allocation task execution time by at least 18.03% compared to traditional methods and enhanced task scheduling efficiency by at least 14.01%. …”
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Optimizing sum rates in IoT networks: A novel IRS-NOMA cooperative system by Mukkara Prasanna Kumar, Ammar Summaq, Sunil Chinnadurai, Poongundran Selvaprabhu, Vinoth Babu Kumaravelu, Md. Abdul Latif Sarker, Dong Seog Han

“…By leveraging our optimization algorithm, the proposed system ensures efficient resource allocation, achieving superior spectral efficiency and fairness among users compared to traditional models. …”
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Coalition Game-Based Reinforcement Learning in Underwater Acoustic Networks by Khouloud Gharsalli, Sameh Najeh, Thierry Le Pors, Leila Najjar, Pierre-Jean Bouvet, Hichem Besbes

“…The purpose of this work is to address the limitations of existing resource allocation strategies that rely on static optimization or centralized control, which lack scalability and adaptability in large, dynamic UWA networks. …”
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Modeling LTE-advanced cell capacity estimation using packet bundling and carrier aggregation by Rajiv Senapati

“…The model proposed in this article explicitly uses some long term evolution (LTE)-Advanced (LTE-A)-specific enhancements such as carrier aggregation (CA) and channel quality indication (CQI)-based resource allocation. Further, this study proposes a CQI-based clustering approach with packet bundling and CA to optimize radio resource utilization and enhance LTE-A cell capacity. …”
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Application of predator-prey optimization for task scheduling in cloud computing by Zahra Jalali Khalil Abadi, Behnam Mohammad Hasani zade, Najme Mansouri, Mohammad Masoud Javidi

“…Cloud computing environments require scheduling to allocate resources efficiently and ensure optimal performance. …”
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Optimization and benefit evaluation model of a cloud computing-based platform for power enterprises by Xueli Yin, Xuguang Zhang, Luyao Pei, Rong Hu, Kaihui Ye, Kangkang Cai

“…The model employs an improved lightweight genetic algorithm combined with an elastic resource allocation strategy to dynamically adapt to task changes across various operational scenarios. …”
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Adaptive building engineering component extraction model based on DSOD by Na Lv, Xuan Yang

“…In summary, it can be seen that the adaptive extraction model of building components constructed by the research has excellent information extraction performance, not only can it improve the efficiency of extracting engineering components, but it can also significantly enhance the decision support ability in construction management, optimize resource allocation, reduce risks, and improve the management efficiency of engineering projects. …”
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A cooperative jamming decision-making method based on multi-agent reinforcement learning by Bingchen Cai, Haoran Li, Naimin Zhang, Mingyu Cao, Han Yu

“…Results show that MA-CJD significantly reduces the time defense units are detected while minimizing jamming resource consumption. Compared with existing algorithms, MA-CJD achieves better solutions, demonstrating its superiority in cooperative jamming scenarios.…”
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A Hierarchical Reinforcement Learning Framework for Multi-Agent Cooperative Maneuver Interception in Dynamic Environments by Qinlong Huang, Yasong Luo, Zhong Liu, Jiawei Xia, Ming Chang, Jiaqi Li

“…To address the challenges of real-time decision-making and resource optimization in multi-agent cooperative interception tasks within dynamic environments, this paper proposes a hierarchical framework for reinforcement learning-based interception algorithm (HFRL-IA). …”
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Flash-Attention-Enhanced Multi-Agent Deep Deterministic Policy Gradient for Mobile Edge Computing in Digital Twin-Powered Internet of Things by Yuzhe Gao, Xiaoming Yuan, Songyu Wang, Lixin Chen, Zheng Zhang, Tianran Wang

“…Offloading decisions and resource allocation problems in mobile edge computing (MEC) emerge as key challenges as they directly impact system performance and user experience in dynamic and resource-constrained Internet of Things (IoT) environments. …”
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Multi-Modal Federated Learning Over Cell-Free Massive MIMO Systems for Activity Recognition by Seyed Mohammad Sheikholeslami, Pai Chet Ng, Jamshid Abouei, Konstantinos N. Plataniotis

“…Additionally, we employ a modified Particle Swarm Optimization (PSO) algorithm for efficient resource allocation. Extensive experiments validate our framework, demonstrating substantial reductions in training time and significant improvements in model performance, particularly an average improvement of 15% and 23% in test accuracy compared to the other fusion models when missing one and two modalities in the inference phase.…”
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Synergizing NOMA and energy harvesting in full duplex mobile edge computing for optimized energy efficiency by Mirza Baber Baig, Taoshen Li, Muhammad Zain Yousaf, Mohit Bajaj, Arvind R. Singh, Milkias Berhanu Tuka

“…Full-duplex base stations simultaneously manage task offloading and energy transmission, improving resource utilization. A Block Coordinate Descent (BCD)-based algorithm addresses the non-convex optimization challenge, offering an optimal solution. …”
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Spatiotemporal pattern analysis of land use in Jiangsu Province based on long-term time series remote sensing images by Zhendong Ji, Lingzhi Yin, Jinhong Wang

“…Studying spatiotemporal patterns of land use is crucial for optimal land resource allocation and sustainable development. This study utilizes the Google Earth Engine (GEE) platform and long-term remote sensing imagery data, selecting Jiangsu Province as a case study area. …”
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FedMEM: Adaptive Personalized Federated Learning Framework for Heterogeneous Mobile Edge Environments by Chen Ximing, He Xilong, Cheng Du, Wu Tiejun, Tian Qingyu, Chen Rongrong, Qiu Jing

“…This framework enhances the resource allocation optimization algorithm by dynamically adjusting the depth of model inference and the bandwidth allocation strategy, which assists devices with limited computational capabilities in completing inference tasks promptly. …”
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Dynamic Scheduling Model of Bike-Sharing considering Invalid Demand by Liu He, Tangyi Guo, Kun Tang

“…System resources allocation optimization through dynamic scheduling is key to improving the service level of bike-sharing. …”
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Intelligent Beam-Hopping-Based Grant-Free Random Access in Secure IoT-Oriented Satellite Networks by Zhongliang Deng, Yicheng Liao

“…This technique utilizes orthogonal resource allocation algorithms to facilitate efficient resource sharing, effectively tackling the irregular and dynamic traffic. …”
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Modeling Relief Demands in an Emergency Supply Chain System under Large-Scale Disasters Based on a Queuing Network by Xinhua He, Wenfa Hu

“…This emergency system is modeled as a minimal queuing response time model of location and allocation. A solution to this complex mathematical problem is developed based on genetic algorithm. …”
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Optimization strategies in NOMA-based vehicle edge computing network by Jianbo DU, Nana XUE, Yan SUN, Jing JIANG, Shulei LI, Guangyue LU

“…Nowadays, vehicular network is confronting the challenges to support ubiquitous connections and vast computation-intensive and delay-sensitive smart service for numerous vehicles.To address these issues, non-orthogonal multiple access (NOMA) and mobile edge computing (MEC) are considered as two promising technologies by letting multiple vehicles to share the same wireless resources, and the powerful edge computing resources were adopted at the edge of vehicular wireless access network respectively.A NOMA-based vehicular edge computing network was studied.Under the condition of guaranteeing task processing delay, the joint optimization problem of task offloading, user clustering, computing resource allocation and transmission power control was proposed to minimize the task processing cost.Since the proposed problem was difficult to solve, it was divided into sub-problems, and a low-complexity and easy-to-implement method was proposed to solve it.The simulation results show that compared with other benchmark algorithms, the proposed algorithm performs well in minimizing costs.…”
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Optimization strategies in NOMA-based vehicle edge computing network by Jianbo DU, Nana XUE, Yan SUN, Jing JIANG, Shulei LI, Guangyue LU

“…Nowadays, vehicular network is confronting the challenges to support ubiquitous connections and vast computation-intensive and delay-sensitive smart service for numerous vehicles.To address these issues, non-orthogonal multiple access (NOMA) and mobile edge computing (MEC) are considered as two promising technologies by letting multiple vehicles to share the same wireless resources, and the powerful edge computing resources were adopted at the edge of vehicular wireless access network respectively.A NOMA-based vehicular edge computing network was studied.Under the condition of guaranteeing task processing delay, the joint optimization problem of task offloading, user clustering, computing resource allocation and transmission power control was proposed to minimize the task processing cost.Since the proposed problem was difficult to solve, it was divided into sub-problems, and a low-complexity and easy-to-implement method was proposed to solve it.The simulation results show that compared with other benchmark algorithms, the proposed algorithm performs well in minimizing costs.…”
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A Blockchain-Based Collaborative Storage Scheme for Roadside Unit Clusters in Social Internet of Vehicles by Dai Hou, Lan Wei, Lei Zheng, Geng Wu, Jiaxing Hu, Chenxi Dong, Xinru Li, Kai Peng

“…Subsequently, the Vehicle Service Priority-based Greedy Block Allocation Algorithm (VSPGBAA) is devised for intra-cluster storage allocation, which considers vehicles’ dwell times and block access probabilities to reduce overall access costs. …”
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