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

Evaluating the Efficiency of Gray Wolf Optimization and Colonial Competition Algorithm in Load Balancing of Distributed Systems by Asghar Molaei-Yeznabad, Amirhossein Dehghani

Subjects: 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

“…Urban land spatial optimization is one of the important issues in urban planning and land resource management. As the speed advancement of urbanization and the continuous increase of population, the rational use of land resources has become the key to sustainable urban development. …”
Get full text

QoS guaranteed multi-user and multi-traffic scheduling algorithm for IEEE 802.16 network by BAI Bo1, CAO Zhi-gang1, CHEN Wei1, I Chih-lin2

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

Algorithmic Approach of Majority Voting With Agents’ Inclusiveness for Facility Resource Matching by Peash Ranjan Saha, Salimur Choudhury, Kai Salomaa

Get full text

Beamforming and resource optimization in UAV integrated sensing and communication network with edge computing by Bin LI, Sicong PENG, Zesong FEI

“…To address the dependence of traditional integrated sensing and communication network mode on ground infrastructure, the unmanned aerial vehicle (UAV) with edge computing server and radar transceiver was proposed to solve the problems of high-power consumption, signal blocking, and coverage blind spots in complex scenarios.Firstly, under the conditions of satisfying the user’s transmission power, radar estimation information rate and task offloading proportion limit, the system energy consumption was minimized by jointly optimizing UAV radar beamforming, computing resource allocation, task offloading, user transmission power, and UAV flight trajectory.Secondly, the non-convex optimization problem was reformulated as a Markov decision process, and the proximal policy optimization method based deep reinforcement learning was used to achieve the optimal solution.Simulation results show that the proposed algorithm has a faster training speed and can reduce the system energy consumption effectively while satisfying the sensing and computing delay requirements.…”
Get full text

Q-LME: Q-learning-based local mutual exclusion algorithm for flying ad hoc networks by Sindhuja S, Mary Anita Rajam V

“…However, resource allocation and token management in FANETs remain unexplored. …”
Get full text

Robust Allocation of FACTS Devices in Coordinated Transmission and Generation Expansion Planning considering Renewable Resources and Demand Response Programs by Sara Mahmoudi Rashid, Ehsan Akbari, Farshad Khalafian, Mohmmad Hossein Atazadegan, Saeid Shahmoradi, Abbas Zare Ghaleh Seyyedi

“…Adaptive robust optimization (ARO) is used to reach suitable models for the active power of renewable resources and power consumption. As a main search algorithm, a hybrid combination of water cycle algorithm (WCA) and ant lion optimization (ALO) is proposed to find the optimum solution with a small standard deviation. …”
Get full text

Optimizing downlink of CR-NOMA resource allocation: A fairness index approach to balancing system performance and energy efficiency by Nahla Nur Elmadina, Rashid A. Saeed, Elmustafa Sayed Ali, Elsadig Saeid, Rania A. Mokhtar

“…This study addresses the challenge of optimizing resource allocation in downlink Non-Orthogonal Multiple Access (NOMA) systems within small-cell networks, focusing on balancing user fairness, energy efficiency, and system performance. …”
Get full text

Max–Min Share-Based Mechanism for Multi-Resource Fair Allocation with Bounded Number of Tasks in Cloud Computing System by Jie Li, Haoyu Wang, Jianzhou Wang, Yue Zhang

“…Finding a fair and efficient multi-resource allocation is a fundamental goal in cloud computing systems. …”
Get full text

A Gain-Computation Enhancements Resource Allocation for Heterogeneous Service Flows in IEEE 802.16 m Mobile Networks by Wafa Ben Hassen, Meriem Afif

“…This method has a crucial role in the resource management and optimization. In a single service access, we propose a dynamic resource allocation algorithm at the physical layer aiming to maximize the cell data rate while ensuring fairness among users. …”
Get full text

Multi-objective optimization of water resources allocation in rift valley lakes basin (Ethiopia): tradeoffs between efficiency and equity by Mulugeta Mohammed, Belete Birhanu, Fentaw Abegaz

“…This study introduces a multi-objective optimization framework using the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) to balance economic efficiency, equity, and environmental sustainability in water allocation. …”
Get full text

Optimizing Competency-Based Human Resource Allocation in Construction Project Scheduling: A Multi-Objective Meta-Heuristic Approach by Bahman Shojaei, Heidar Dashti Naserabadi, Mohammad Javad Taheri Amiri

“… Effective allocation of human resources to project activities is crucial in optimizing project schedules and resource utilization. …”
Get full text

Intelligent Resource Allocation for Immersive VoD Multimedia in NG-EPON and B5G Converged Access Networks by Razat Kharga, AliAkbar Nikoukar, I-Shyan Hwang

“…This research examines intelligent resource allocation for IVoD services across NG-EPON and B5G X-haul converged networks. …”
Get full text

Adaptive Resource Allocation and Mode Switching for D2D Networks With Imperfect CSI in AGV-Based Factory Automation by Safiu A. Gbadamosi, Gerhard P. Hancke, Adnan M. Abu-Mahfouz

“…The ARAMS scheme integrates mode switching (MS), channel-quality factor (CQF), and power control (PC) within a bi-phasic resource-sharing (RS) algorithm to lower the computational complexity. …”
Get full text