Security-driven service caching and computation offloading strategy in air-ground collaborative edge computing networks by WU Mengru, KONG Yawei, HAN Huimei, LU Haiquan, SI Peiyuan, LU Weidang, GUO Lei

“…Considering dual secrecy rate constraints and resource limitations suffered by a UAV server, UAV service caching, computation offloading decisions of ground devices, resource allocation, and UAV deployment were jointly optimized to minimize the task completion delay of ground devices. …”
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Rescheduling of Multi-Scenario and Multi-Objective Dynamic Changes of Ship Group Construction by ZHANG Aoyuan, HU Xiaofeng, ZHANG Yahui

“…First, the objective function is selected based on different production stage and abnormal disturbance, and a mathematical model is then developed, incorporating site constraints, task precedence constraints, and human resource constraints. Next, a site allocation algorithm is introduced, and an improved non-dominated sorting algorithm based on reference points is adopted to solve the problem. …”
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Semantic aware intelligent optimization for IRS/UAV-enabled MEC in wideband cognitive radio networks by Wei Zheng, Pengshan Ren, Qing Li

“…The proposed semantic-aware optimization framework incorporates semantic information to achieve more efficient task scheduling and resource allocation. Particularly, the proposed optimization framework jointly optimizes UAV trajectories, subcarrier allocation, IRS reflection coefficients, task offloading ratios, task priorities and contextual relevance to maximize semantic utility and system energy efficiency while dynamically ensuring task demands. …”
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User Random Access Technology Based on Beam Hopping Satellite Communication System by Zixuan HUANG, Jiaxi ZHOU, Jing ZHANG, Zhengyu ZHANG

“…On the basis of geosynchronous earth orbit multi-beam satellite communication systems, this paper designed the process of user random access to the network and specifi c signaling interaction under the agile beam mechanism, and proposed the scheduling strategy and allocation scheme of the agile signaling beam.This scheme increased the fl exibility of access resource allocation under the premised of ensured that all users could accessed the network, eff ectively improved the utilization rate of satellite network resources.The request of user access to the satellite communication network belongs to the burst type, it is more suitable to use the random competition access, so this paper based on the general random competition access strategy, proposed an adaptive random competition access algorithm based on the heat value, based on the heat value predicted by the network side, the user selects diff erent random access strategies for access.Through the simulation and analysis of the optimization algorithm, it is proved that the algorithm could eff ectively reduced the probability of access collision under various network loads, so as to achieved the purpose of users quickly accessing the network.…”
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Group Stable Matching Problem in Freight Pooling Service of Vehicle–Cargo Matching Platform by Linlin Kong, Min Huang

“…As a result, they significantly improve the intelligence and precision of logistics resource allocation. However, at the current stage, vehicle–cargo matching platforms rarely promote freight pooling services, leading to resource underutilization. …”
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Optimization, Design, and Implementation of Biodiversity-Focused Fisheries Survey Stations: A Case Study of the Coastal Waters of Maoming by Yuexiu DENG, Yongheng HUANG, Jianyu DONG, Ning CHEN, Jing ZHANG, Xuefeng WANG

“…This package, based on a genetic algorithm, can determine the optimal stratification, sample size, and sample allocation to meet precision constraints in the presence of multiple stratification variables and multiple target variables. …”
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Integer-Linear-Programing Optimization in Scalable Video Multicast with Adaptive Modulation and Coding in Wireless Networks by Dongyul Lee, Chaewoo Lee

“…However, because of the sharing nature of the wireless medium, efficient resource allocation has been studied to achieve a high level of acceptability and proliferation of wireless multimedia. …”
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Deep Learning-Driven Geospatial Modeling of Elderly Care Accessibility: Disparities Across the Urban-Rural Continuum in Central China by Yi Yu, Tian Dong

“…Taking Changsha as a case study, this research constructs an accessibility evaluation system based on the 15-min life circle theory, utilizing multi-source data. Spatial weighting characteristics of elderly care facility locations were analyzed through machine learning algorithms, and service coverage disparities between urban districts and suburban towns were assessed under 5-, 10-, and 15-min walking thresholds. …”
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Integrating Machine Learning for Enhanced Agricultural Productivity: A Focus on Bananas and Arecanut in the Context of India’s Economic Growth by B. S. Saruk, G. Mokesh Rayalu

“…Assist yield projections may provide governments and policymakers with valuable information to make well-informed choices about food security, import–export policies, and resource allocation. It facilitates national- and regional-level food supply planning. …”
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Deep Reinforcement Learning-Based Two-Phase Hybrid Optimization for Scheduling Agile Earth Observation Satellites by Guanghui Zhou, Zhicheng Jin, Dongning Liu

“…To mitigate problem complexity, the action space is decomposed into two interdependent decision layers: task sequencing and resource allocation. Given the resource occupation constraints during action execution, a novel reward function is designed by integrating resource occupation utility into the immediate reward mechanism. …”
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Buffer-aided cooperative NOMA with power transfer by Long YANG, Li ZHAO, Yuchen ZHOU, Bingtao HE, Jian CHEN

“…To improve the throughput of multiuser simultaneous wireless information and power transfer systems, a buffer-aided cooperative non-orthogonal multiple access scheme with power transfer was designed to maximize the average throughput under the constraints of average/peak power, user’s rate, and the buffer stability.To reduce the optimization complexity, the Lyapunov’s method was introduced to convert the long-term average optimization problem into a series of time-discrete subproblems, and an adaptive transmission and resource allocation optimization algorithm was proposed, where the working mode, the user scheduling and the power allocation were dynamically optimized according to the time-varying channel/buffer state.Simulation results demonstrate that compared with the existing schemes, the proposed scheme can significantly enhance the average throughput whilst achieving the tradeoff between the delay and throughput.…”
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Gemini: A Cascaded Dual-Agent DRL Framework for Task Chain Planning in UAV-UGV Collaborative Disaster Rescue by Mengxuan Wen, Yunxiao Guo, Changhao Qiu, Bangbang Ren, Mengmeng Zhang, Xueshan Luo

“…Specifically, this framework comprises a chain selection agent and a resource allocation agent: The chain selection agent plans paths for task chains, and the resource allocation agent distributes platform loads along generated paths. …”
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Secure communication approach for Internet of things based on C-RAN fronthaul compression by Yong WANG, Mu ZHOU, Zengshan TIAN, Jinjun WU

“…A resource allocation algorithm was proposed for downlink C-RAN secure communication system.This algorithm jointly optimized the parameters of base station (BS) mode,quantized noise and beamforming under the constraints of SINR requirements of Internet of things information receiver,eavesdropped receiver and fronthaul link capacity.Such a design was a non-convex optimization problem,and a step-by step optimization algorithm was proposed to decompose the original optimization problem efficiently.Semi-definite technique and function smoothing approach were adopted,and the local optimization solution of the original problem was obtained by the iterative different of convex method.Bi-section approach was further proposed to determine BS mode,and the transmitting power of the BSs were finally optimized.Simulation results indicate that the proposed joint optimization algorithm achieves better performance than group sparse optimization algorithm and baseline algorithm,and it has approximate optimal performance as the exhaustive search algorithm.…”
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Robustness Maximization of Parallel Multichannel Systems by Jean-Yves Baudais, Fahad Syed Muhammad, Jean-François Hélard

“…Simulation results confirm the asymptotic convergence of both resource allocation policies. In nonasymptotic regime the resource allocation policies can be interchanged depending on the robustness measure and on the operating point of the communication system. …”
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Challenges and inequalities in the management of financing the tasks of local government units: a critical analysis by Arkadiusz Ciach

“…Do the currently used algorithms for the distribution of subsidies reflect the real needs of local government units, and, as a result, there is an optimal allocation of public funds? …”
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Optimization strategy of multi-link energy efficient joint transmission of Wi-Fi 7 by Linyan DAI, Xuming FANG, Rong HE

“…In the multi-link non-simultaneous transmit and receive mode of next-generation Wi-Fi 7 protocol, the transmission ending time of multi-link device (MLD) needs to be aligned on each link, which may require data padding, resulting in the waste of spectrum resources and transmission energy consumption.A high energy efficient MLD transmission algorithm was proposed to improve the total energy efficiency of MLD station (STA) on the premise of meeting the data transmission delay limit.The proposed algorithm was optimized from the following three aspects: link data distribution ratio, communication resource allocation and STA transmission power.Simulation results show that the proposed algorithm can reduce energy consumption by reducing padding data on the premise of guaranteeing the delay limit of data transmission, and the transmission energy efficiency of the system is increased by about 150% compared with that of the baseline scheme.…”
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Premier Dynamic Bandwidth Management and Tensile Wavelength Selection Ensuring QoS for NG-EPONs by Purushottam Singh, Pushpendra Kumar, Harshita Patel, Kanojia Sindhuben Babulal, Gayathri Ananthakrishnan

“…Comparative analysis reveals that TW-DBA outperforms existing algorithms like Flexible Wavelength (FW), First-Fit, and Water Filled, both in computational efficiency and resource allocation. …”
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Study on multi-satellite cooperative spectrum cognitive method integrating Stackelberg game and federated learning by Xiaojin DING, Yehui XU, Wen BAO, Gengxin ZHANG

“…To solve the problem of the weak spectrum-cognitive ability caused by monitoring angle, direction resolution, limited processing ability and peak power for a low-earth-orbit (LEO) satellite, a multi-satellite cooperative spectrum cognitive method integrating Stackelberg game and federated learning was proposed.Firstly, considering the available computing resource, cognitive performance, processing and transmission delay of each spectrum cognitive satellite, a cooperative-satellite selection and computing-resource allocation algorithm was built for multiple spectrum-cognitive tasks.Secondly, based on the selected satellites and the allocated computing resources, a low-complexity multi-satellite cooperative spectrum cognitive strategy was further designed, which could automatically sense the spectrum holes, and detect interference as well as identify the modulation mode.Simulation results demonstrate that compared to the single-node cognitive method, the designed multi-satellite cooperative spectrum cognitive strategy can obtain a better cognitive performance.Moreover, comparing with the existing model, the model utilized in the designed strategy can effectively achieve 96.69% and 93.32% lower number of parameters and required floating point operations per second, whilst maintaining the performance.…”
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Research on deep reinforcement learning in Internet of vehicles edge computing based on Quasi-Newton method by ZHANG Jianwu, LU Zetao, ZHANG Qianhua, ZHAN Ming

“…To address the issues of ineffective task offloading decisions caused by multitasking and resource constraints in vehicular networks, the Quasi-Newton method deep reinforcement learning dual-phase online offloading (QNRLO) algorithm was proposed. …”
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Joint Caching and Computation in UAV-Assisted Vehicle Networks via Multi-Agent Deep Reinforcement Learning by Yuhua Wu, Yuchao Huang, Ziyou Wang, Changming Xu

“…This requires balancing system energy consumption and resource allocation fairness while maximizing cache hit rate and minimizing task latency. …”
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