Edge computing smart grid resource scheduling algorithm based on reinforcement learning by Jinghang YU, Yichen ZHAO, Hu SONG

“…A smart grid is a power network capable of intelligent management and optimization.Network virtualization technology can effectively improve the resource utilization and reliability of smart grids and meet the differentiated needs of different users.In the case of limited resources, traditional virtual network embedding algorithms cannot dynamically adjust the allocation and mapping of virtual resources according to the resource usage and user needs of the power system.To solve this problem, edge computing and virtualization technology was combined and a virtual network resource scheduling algorithm based on reinforcement learning was introduced.The simulation results show that the proposed virtual resource scheduling algorithm is better than the other three scheduling algorithms in improving power grid reliability and resource utilization.…”
Get full text

ML-RASPF: A Machine Learning-Based Rate-Adaptive Framework for Dynamic Resource Allocation in Smart Healthcare IoT by Wajid Rafique

Get full text

Power Grid Clock Synchronization Optimization Based on Stackelberg Game Theory by Jiahao Li, Yitao Zhao, Yiming Zhang, Zhiyu Xia, Chuanxu Chen, Quansheng Guan

“…Finally, the simulation results are given in MATLAB to prove that the proposed method can converge quickly and dynamically adjust allocation according to user demand. Furthermore, the network simulator Mininet and the open-source software-defined network framework Ryu are used to evaluate the performance of the proposed method. …”
Get full text

A Task Offloading and Resource Allocation Strategy Based on Multi-Agent Reinforcement Learning in Mobile Edge Computing by Guiwen Jiang, Rongxi Huang, Zhiming Bao, Gaocai Wang

“…Task offloading and resource allocation is a research hotspot in cloud-edge collaborative computing. …”
Get full text

Energy Aware Optimal Resource Allocation in Backhaul Constraint Wireless Networks: A Two Base Stations Scenario by Yuan Gao, Peng Xue, Yi Li, Hongyi Yu, Xianfeng Wang, Shihai Gao

“…Simulations show that this allocation algorithm can improve the system capacity and energy efficiency significantly compared with the blind alternatives.…”
Get full text

Energy-Efficient Multi-Agent Deep Reinforcement Learning Task Offloading and Resource Allocation for UAV Edge Computing by Shu Xu, Qingjie Liu, Chengye Gong, Xupeng Wen

“…This paper proposes a novel multi-agent reinforcement learning framework, termed Multi-Agent Twin Delayed Deep Deterministic Policy Gradient for Task Offloading and Resource Allocation (MATD3-TORA), to optimize task offloading and resource allocation in UAV-assisted MEC networks. …”
Get full text

Power-Efficient UAV Positioning and Resource Allocation in UAV-Assisted Wireless Networks for Video Streaming with Fairness Consideration by Zaheer Ahmed, Ayaz Ahmad, Muhammad Altaf, Mohammed Ahmed Hassan

“…The joint optimization includes power minimization, efficient resource allocation, i.e., transmit power and bandwidth, and efficient two-dimensional positioning of the UAV while meeting system constraints. …”
Get full text

Network Resource Allocation Method Based on Awareness–Prediction Joint Compensation for Low-Earth-Orbit Satellite Networks by Hang Di, Tao Dong, Zhihui Liu, Shuotong Wei, Qiwei Zhang, Dingyun Zhang

“…Furthermore, an efficient, accelerated alternating-direction method of multipliers (ADMM) resource allocation algorithm is proposed with the aim of maximizing the satisfaction of service resources requirements. …”
Get full text

Research on the generalized utility max-min fair algorithm based on piecewise linear function by XU Tong, LIAO Jian-xin

Subjects: Get full text

SPYDER: QoS-Aware Radio Resource Allocation in Multiuser ISAC-Capable C-V2X Networks by Syed Najaf Haider Shah, Aamir Ullah Khan, Christian Schneider, Joerg Robert

“…To counteract this, we employ sparse reconstruction algorithms within the compressed sensing framework, enhancing flexibility in TF resource allocation and providing high-resolution radar sensing despite uncoordinated resource selection. …”
Get full text

Mode selection and resource optimization for UAV-assisted cellular networks by Daquan FENG, Canjian ZHENG, Xiangqi KONG

“…The resource allocation and optimization scheme was studied in a coexistence scenario of unmanned aerial vehicle (UAV) and cellular communication network.To improve spectrum efficiency of the system, UAV users could reuse the cellular spectrum resources to access the network through full duplex or half duplex device-to-device technique.Additionally, a joint access control, mode selection, power control and resource allocation optimization problem was formulated to maximize the overall throughput of the network while ensuring quality of service requirements for both UAV users and ground cellular users.Specifically, the phase 1 method in the convex optimization was adopted for access control and feasibility check, and then the convex and concave procedure (CCCP) iterative algorithm was used to solve the power control problem for feasible UAV user pairs.By using this local optimum value, the original optimization problem can be simplified into a weighted maximization problem.Finally, the Kuhn-Munkres (KM) algorithm was used to match the optimal channel resources and obtain the global optimal throughput value of the system.Numerical results show that the proposed scheme can significantly improve the performance of system.…”
Get full text

Deep Reinforcement Learning for Resource Constrained Multiclass Scheduling in Wireless Networks by Apostolos Avranas, Philippe Ciblat, Marios Kountouris

“…Our method can, for instance, achieve with 13% less power and bandwidth resources the same user satisfaction rate as a myopic algorithm using knapsack optimization.…”
Get full text

Flow Allocation Algorithm Based on Potential Game in Multi-Source Multi-Hop Wireless Sensor Network by Wei Zhang, Linghua Zhang

Get full text

Optimal allocation of urban land space based on NSGA2 by Yi Guo, Chaoqin Bai, Peiwen Zhao

“…Meanwhile, the reverse iteration distance value of this algorithm was only 4.14%, which was 22.76% lower than the adaptive weighted genetic algorithm. …”
Get full text

Dynamic Beam Hopping Algorithm for LEO Satellite Systems Based on User Grouping by Qing SHU, Weibiao LI, Zuolin JIN, Zhong ZHENG, Yongbo ZHANG, Zesong FEI

Get full text

Implications of algorithmic bias in AI-driven emergency response systems by Katsiaryna Bahamazava

Subjects: Get full text

Deep reinforcement learning-based resource reservation algorithm for emergency Internet-of-things slice by Guolin SUN, Ruijie OU, Guisong LIU

“…Based on the requirements of ultra-low latency services for emergency Internet-of-things (EIoT) applications,a multi-slice network architecture for ultra-low latency emergency IoT was designed,and a general methodology framework based on resource reservation,sharing and isolation for multiple slices was proposed.In the proposed framework,real-time and automatic inter-slice resource demand prediction and allocation were realized based on deep reinforcement learning (DRL),while intra-slice user resource allocation was modeled as a shape-based 2-dimension packing problem and solved with a heuristic numerical algorithm,so that intra-slice resource customization was achieved.Simulation results show that the resource reservation-based method enable EIoT slices to explicitly reserve resources,provide a better security isolation level,and DRL could guarantee accuracy and real-time updates of resource reservations.Compared with four existing algorithms,dueling deep Q-network (DQN) performes better than the benchmarks.…”
Get full text

Designing a Multiobjective Human Resource Scheduling Model Using the Tabu Search Algorithm by Roghayeh Mirataollahi olya, Seyed Ahmad Shayannia, Mohammad Mehdi movahedi

“…In this research, considering the high importance of these issues, the problems of scheduling and allocation of manpower in a real place are solved. To this end, the metaheuristic Tabu search algorithm is used with the aim of minimizing the duration of activity and the presence of all manpower. …”
Get full text

A FPGA Accelerator of Distributed A3C Algorithm with Optimal Resource Deployment by Fen Ge, Guohui Zhang, Ziyu Li, Fang Zhou

“…In addition, the resource wastage problem caused by the distributed training characteristics of A3C algorithms and the resource allocation problem affected by the imbalance between the computational amount of inference and training need to be carefully considered when designing accelerators. …”
Get full text

Educational resources recommendation algorithm based on GMF-MLP-NeuMF prediction model by Rui Wang, Qiusheng Cui, Yezhi Xiao, Jinfeng Du, Ruicheng Yue

Get full text