Joint Optimization of Resource Allocation and Task Offloading Strategies in Multi-Cell Dynamic MEC Systems Using Multi-Agent DRL by Yuntao Hu, Ming Chen, Haowen Sun, Yinlu Wang, Yihan Cang

“…The energy consumption minimization is achieved by jointly optimizing the task offloading proportions, transmit power allocations, and computational resource distributions while ensuring the overall deadline constraints and the minimum processing size requirements in each scheduling cycle. …”
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Efficient resource allocation for D2D-enabled social IoT networks: A tripartite and time-scale optimization approach by Saurabh Chandra, Rajeev Arya, Maheshwari Prasad Singh

“…The problem is solved in two stages: a tripartite graph-based resource allocation stage and a time-scale optimization stage. …”
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DCOOL: Dynamic computation offloading and resource allocation for LEO satellite-assisted edge computing in a ground-space integrated framework by Jeonghwan Kim, Jeongho Kwak

“…To this end, this paper introduces a dynamic computation offloading and resource allocation framework in the LEO satellite MEC architecture. …”
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A Multi-Objective Dynamic Resource Allocation Model for Search and Rescue and First Aid Tasks in Disaster Response by Employing Volunteers by Emine Nisa Kapukaya, Sule Itir Satoglu

“…Pre-disaster planning and post-disaster dynamic resource allocation including material and human resources is essential. …”
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Simultaneous Optimal Allocation of EVCSs and RESs Using an Improved Genetic Method by Majid Farjamipur, Hossein Lotfi, Mohammad Hassan Nikkhah

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A deep learning and IoT-driven framework for real-time adaptive resource allocation and grid optimization in smart energy systems by Arvind R. Singh, M. S. Sujatha, Akshay D. Kadu, Mohit Bajaj, Hailu Kendie Addis, Kota Sarada

“…Abstract The rapid evolution of smart grids, driven by rising global energy demand and renewable energy integration, calls for intelligent, adaptive, and energy-efficient resource allocation strategies. Traditional energy management methods, based on static models or heuristic algorithms, often fail to handle real-time grid dynamics, leading to suboptimal energy distribution, high operational costs, and significant energy wastage. …”
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Toward Optimal Resource Allocation: A Multi-Agent DRL Based Task Offloading Approach in Multi-UAV-Assisted MEC Networks by Muhammad Naqqash Tariq, Jingyu Wang, Salman Raza, Mohammad Siraj, Majid Altamimi, Saifullah Memon

“…However, the growing number of UAVs and smart devices causing a major difficulty in the devising an effective scheme for the task offloading and resource allocation in multi-UAV-aided MEC networks. …”
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Intelligent Dynamic Multi-Dimensional Heterogeneous Resource Scheduling Optimization Strategy Based on Kubernetes by Jialin Cai, Hui Zeng, Feifei Liu, Junming Chen

“…In this paper, we tackle the challenge of optimizing resource utilization and demand-driven allocation in dynamic, multi-dimensional heterogeneous environments. …”
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Leveraging Artificial Intelligence for Smart Healthcare Management: Predicting and Reducing Patient Waiting Times with Machine Learning by Kristijan CINCAR, Todor IVAŞCU

“… The paper focuses on a machine-learning-based methodology for predictive modelling and simulation enhancement of hospital resource management. The proposed system is built on a multitude of machine-learning algorithms such as Random Forest Regression, XGBoost, Support Vector Regression (SVR), and Artificial Neural Networks (ANNs) to render accurate estimations of patient waiting times. …”
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Algorithm on joint optimization of power allocation and slot allocation in satellite communication systems by Han HAN, Ying LI, Xu DONG, Xiao-bo GUO, Qin-fei HUANG

“…An algorithm to jointly optimize the power allocation and the slot allocation in order to improve the utilization efficiency of the limited resources on the satellite was proposed.The basic principles of the mutual compensation and mutual independence between these two resources are explored to pave the way for joint optimization.Considering the differences about each station’s channel condition and capacity requirement,a state-combination model for optimally allocating the resources is setted up,so as to adapt the multi-resource usage pattern with each earth station.Targeting at the energy efficiency,an iterative dual optimization algorithm is proposed,and the final optimal policy for resource allocation with low complexity is obtained.With the simulation and analysis,the proposed joint optimization is verified to perform better than the non-joint ones in the perspective of the energy efficiency,especially when the frequency resource (the carrier number) is less.…”
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An Improved Dingo Optimization for Resource Aware Scheduling in Cloud Fog Computing Environment by Santhosh Kumar Medishetti, Ganesh Reddy Karri

“…Task scheduling in Cloud-Fog computing environments is a critical aspect of optimizing resource allocation and enhancing performance. This study presents an improved version of the Dingo Optimization Algorithm (IDOA) specifically designed for task scheduling in Cloud-Fog computing. …”
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Resource Scheduling in MU-MIMO and NOMA Enabled Integrated Access and Backhaul Networks by Chuan-Wei Cho, Meng-Shiuan Pan

“…The designed two-phase algorithm has the following features: 1) support for multi-path routing and efficient resource utilization through the combined use of MU-MIMO and NOMA, 2) a novel route decision phase that selects optimal paths by considering load balancing among IAB nodes, and 3) a dynamic link scheduling phase that allocates transmission power and schedules links to maximize network capacity. …”
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Multi-domain optical network virtual technology based on SDN by Shidong LIU, Pan WANG

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A traffic-awareness dynamic resource allocation scheme based on multi-objective optimization in multi-beam mobile satellite communication systems by YuanZhi He, YiZhen Jia, XuDong Zhong

“…Since the dynamic resource allocation problem is formulated as NP-hard, a new traffic-aware dynamic resource allocation (TADRA) algorithm is proposed. …”
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Spatially optimized allocation of water and land resources based on multi-dimensional coupling of water quantity, quality, efficiency, carbon, food, and ecology by Yingbin Wang, Haiqing Wang, Jiaxin Sun, Peng Qi, Wenguang Zhang, Guangxin Zhang

“…The COM-WL model integrates our improved genetic algorithm, PAEA-NSGAⅢ, with the landscape allocation model, GridLOpt. …”
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Time deterministic routing algorithm and protocol based on time-varying graph over the space-ground integrated network by Hongyan LI, Tao ZHANG, Jingqian ZHANG, Keyi SHI, Pengcheng ZENG

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A hybrid machine learning model with self-improved optimization algorithm for trust and privacy preservation in cloud environment by Himani Saini, Gopal Singh, Sandeep Dalal, Iyyappan Moorthi, Sultan Mesfer Aldossary, Nasratullah Nuristani, Arshad Hashmi

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Cooperative communication resources scheduling of satellite network using a mixed vector encoding heuristic algorithm by Jiaxuan Xie, Linling Kuang, Shan Gao

“…In this paper, we propose a mixed vector encoding heuristic algorithm (MVEHA) to optimize the joint resources allocation problem of the multiple beams satellite network. …”
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Joint Resource Allocation and Power Control in Rate-Splitting Multiple Access-Based Integrated Terrestrial and Non-Terrestrial Networks With HAP Assistance by Thong-Nhat Tran, Young Jeon, Heejung Yu, Taejoon Kim

“…The non-convex JRPS problem is reformulated as a linear program and solved using an iterative successive convex approximation algorithm that ensures local optimality. Additionally, a heuristic resource allocation and power control method is also proposed to provide an effective initialization for JRPS and to serve as a performance baseline. …”
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A downlink resource scheduling strategy for C-RAN backhaul network by WANG Ru-yan, ZHOU Jing, WU Da-peng

“…According to the network demand of wireless users in hot spots, three optimization objectives including the number of used wavelengths, load balance, and well-distribution of real-time traffic were considered in the optimization of adaptive-weighted parallel genetic algorithm. Thus, the wavelength resources were dynamically allocated and resource utilization was improved. …”
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