Minimization of Resource Consumption with URLLC Constraints for Relay-Assisted IIoT by Yujie Zhao, Tao Peng, Yichen Guo, Yijing Niu, Wenbo Wang

“…At peak rates, the hop with superior channel conditions requires fewer resources. Compared with three baseline algorithms, the proposed algorithm achieves average resource savings of 21.40%, 14.03%, and 17.18%, respectively.…”
Get full text

Successive relaying secure transmission scheme based on inter-relay interference cancellation by Yi ZOU, Kai-zhi HUANG, Xiao-lei KANG

“…A secure scheme based on inter-relay interference cancellation was proposed to solve untrusted relay eavesdropping problem in successive relaying systems.First inter-relay interference between trusted relay and untrusted relay was exploited as artificial noise to degrade untrusted relay’s eavesdropping condition,then interference iterative cancellation was adapted to improve signal quality at legitimate user by making use of correlation between signals in time domain.Based on this,a quick power allocation algorithm aiming to minimize untrusted relay’s sum rate was proposed.Analysis and simulation results show that the proposed scheme suppress untrusted relay’s eavesdropping without loss of communication efficiency,a promotion of at least 2 bit·s^-1·Hz^-1in secrecy rate can be observed.…”
Get full text

Intelligent resource scheduling scheme for UAV swarm collaborative sensing by ZHAO Pengcheng, LI Tianyang, LENG Supeng, XIONG Kai

“…Adaptive sensing mode selection, stepwise computation offloading, and competitive bandwidth allocation were integrated to achieve heterogeneous resource coordination across communication, sensing, and computation (CSC), thereby enhancing collaborative sensing efficiency. …”
Get full text

Resource trading strategies with risk selection in collaborative training market. by Quyuan Wang, Xinyu Ni, Yuping Tu, Ying Wang, Jiadi Liu

“…While prior research has addressed technical aspects of resource allocation, less attention has been paid to the underlying economic mechanisms of resource trading. …”
Get full text

Power allocation satisfying user fairness for integrated sensing and communication system based on orthogonal time frequency space modulation by Ke XU, Luping XIANG, Jie HU, Kun YANG

“…By sharing resources for radar sensing and communications, integrated sensing and communication (ISAC) has promising applications in diverse scenarios, such as human-machine interface, vehicle-to-everything (V2X), remote sensing, and environment surveillance.In order to resolve the frequency resource conflict in high-speed V2X networks, based on the modulation orthogonal time frequency (OTFS), the OTFS-ISAC system was proposed, where the base station receives reflected echoes to obtain sensing parameters of vehicle motion and then establish the vehicle’s mobile topology.Additionally, in terms of the multi-vehicle network, the design of OTFS-ISAC with NOMAsatisfying the fairness and the algorithm of power allocation were proposed.Simulations show that compared with the NOMA without radar sensing system, the proposed design improves the system data rate by 25%.…”
Get full text

An Integrated Electricity–Gas–Heat Energy System Based on the Synergy of Long- and Short-Term Energy Storage by Min Zhang, Jinhao Wang, Huiqiang Zhi, Jun Zhao, Xiao Chang, Shifeng Zhang, Xiangyu Guo, Tengxin Wang

“…Firstly, an adaptive noise integration empirical modal decomposition method based on the optimization improvement of the grey wolf algorithm is designed for the power allocation strategy of the hybrid energy storage system; secondly, for the electric–gas system, an energy management strategy for the hybrid electric–gas energy storage system, taking into account the operating characteristics of the alkaline electrolyzer, is proposed in order to strengthen the complementary mechanism between electric energy storage and gas energy storage. …”
Get full text

Static and Dynamic Routing, Fiber, Modulation Format, and Spectrum Allocation in Hybrid ULL Fiber-SSMF Elastic Optical Networks by Kangao Ouyang, Fengxian Tang, Zhilin Yuan, Jun Li, Yongcheng Li

“…To address this issue, the ultra-low loss and large effective area (ULL) fibers are successfully manufactured and expected to deployed in the existing optical networks. …”
Get full text

Deep reinforcement learning based resource provisioning for federated edge learning by Xingyun Chen, Junjie Pang, Tonghui Sun

“…The MFLD algorithm leverages Deep Reinforcement Learning (DRL) techniques to automatically select UEs and allocate the computation resources according to the task requirement. …”
Get full text

Blockchain-based heterogeneous resource configuration scheme in computing power network by Qiang Gao, Chunyu Liu, Lei Wang, Yiqing Liu, Yueqiang Xu

“…However, efficiently allocating these resources to achieve an optimal balance between system energy consumption and latency, as well as ensuring the security of the resource allocation process, remain significant challenges. …”
Get full text

Reconfigurable intelligent surface assisted resource optimization method for heterogeneous network by Xianhao SHEN, Ziling ZENG, Shaohua NIU

“…For reconfigurable intelligent surface (RIS)-assisted heterogeneous network slicing, a resource optimization method with joint resource allocation and phase shift optimization was proposed.A joint optimization problem with different objectives was constructed for different services in heterogeneous networks.For enhanced mobile broadband (eMBB) services, the resource block allocation, power allocation and RIS phase shift matrix were jointly optimized based on the alternating optimization algorithm to maximize the total traversal capacity of eMBB users.For ultra-reliable low-latency communication (URLLC) services, a pre-configured RIS-based heuristic URLLC allocation algorithm was proposed with the objectives of maximizing the URLLC packet reception rate and minimizing the amount of eMBB rate loss.Simulation results demonstrate that the proposed algorithm achieves about 99.99% URLLC packet reception rate using only 80 RISs compared to 95.95% URLLC packet reception rate when no RISs are deployed, while the total eMBB rate is increased by 86.24%.…”
Get full text

Scalable Resource Provisioning Framework for Fog Computing Using LLM-Guided Q-Learning Approach by Bhargavi Krishnamurthy, Sajjan G. Shiva

Get full text

The Impact of Prediction Models on Energy-Aware Resource Management in FaaS Platforms by Shahrokh Vahabi, Francesca Righetti, Carlo Vallati, Nicola Tonellotto

“…Moreover, resource allocation performed through the EA-RM algorithm reduces the energy consumption by ~12-45% on average w.r.t. competitors, and is proven to be more robust w.r.t. the accuracy of the prediction model used.…”
Get full text

A Hierarchical Control Framework for Coordinating CAV-Dedicated Lane Allocation and Signal Timing at Isolated Intersections in Mixed Traffic Environments by Feng Chen, Cunbao Zhang, Yu Cao

“…The framework employs two collaborative agents based on the dueling double deep Q-network (D3QN) algorithm. The upper-level agent recommends optimal CAV-DLs configurations based on long-term traffic flow patterns, while the lower-level agent focuses on real-time signal control by adjusting signal parameters and green time allocations in response to current traffic demand. …”
Get full text

Study on distributed and dynamic resource management for delay-sensitive sensor network by Wei LIU, Jun LIU

“…The delay-aware dynamic resource management problem was investigated in sensor network,with a focus on resource allocation among the sensors and power control along the time.By taking account of average delay requirements and power constraints,the considered problem was formulated into a stochastic optimization problem.Inspired by Lyapunov optimization theory,the intractable stochastic optimization problem was transformed into a tractable deterministic optimization problem,which was a mixed-integer resource management problem.By exploiting the specific problem structure,the mixed-integer resource management problem was equivalently transformed into a single variable problem,and the cooperative distributed method was present to effectively solve it with guaranteed global optimality.Finally,a dynamic resource management algorithm was proposed to solve the original stochastic optimization problem.Simulation results show the performance of the proposed dynamic algorithm and reveal that there exists a fundamental tradeoff between delay requirements and power consumption.…”
Get full text

Next-Gen Internet of Drones: Federated Learning and Digital Twin Synergy for Energy-Efficient Task Allocation and Seamless Service Migration by Ahmad Arsalan, Tariq Umer, Rana Asif Rehman, Byung-Seo Kim

Get full text

Hybrid Blockchain-Based Multi-Operator Resource Sharing and SLA Management by Sidra Tul Muntaha, Qasim Z. Ahmed, Faheem A. Khan, Zaharias D. Zaharis, Pavlos I. Lazaridis

“…Results demonstrate the framework’s effectiveness in enhancing resource allocation and SLA enforcement in 5G networks, highlighting the capabilities of different blockchain platforms in managing complex network operations.…”
Get full text

Domain-weighted transfer learning and discriminative embeddings for low-resource speaker verification by Han Wang, Mingrui He, Mingjun Zhang, Changzhi Luo, Longting Xu

“…In this paper, we propose a domain-weighted allocation fine-tuning strategy that employs the Kernel Mean Matching (KMM) algorithm to adjust the distribution differences between the in-domain and out-of-domain datasets. …”
Get full text

AI and Human Resources in a Literature-Driven Investigation Into Emerging Trends by Cristina Iancu, Simona-Vasilica Oprea

“…The analysis brings out a steady growth in publication volume, with an average of 2,500 papers annually and a significant concentration of research within domains such as neural networks, algorithm optimization and digital transformation. …”
Get full text

Demand Prediction of Railway Emergency Resources Based on Case-Based Reasoning by Jianping Sun, Hantao Cao, Biao Geng, Zhaoping Tang, Xiaopeng Li

“…The demand prediction of emergency resources is helpful for rational allocation and optimization of emergency resources for railway rescue when emergency incident occurs. …”
Get full text

Model Identification, Dynamic Positioning, and Thrust Allocation System for the milliAmpere1 Autonomous Ferry Prototype: Field Trial Results by Miguel Hinostroza, Camilla Fruzzetti, Andreas Gudahl Tufte, Simon J. N. Lexau, Alexey Gusev, Egil Eide, Edmund F. Brekke, Anastasios M. Lekkas, Roger Skjetne, Michele Martelli, Morten Breivik

“…At the same time, the TA algorithm coordinates the thrusters to ensure that the resulting force they generate matches the request from the DP control algorithm. …”
Get full text