Article
Computer Science, Artificial Intelligence
Himanshu Gupta, Om Prakash Verma
Summary: This study proposes a novel hybrid optimizer (HCPSOA) for unmanned aerial vehicles (UAVs) by combining Particle Swarm Optimization (PSO) and Coyote Optimization Algorithm (COA). The chaotic logistic map and dynamic weight adjustments are incorporated to enhance exploration-exploitation capabilities. The results show that HCPSOA outperforms other algorithms in accurately estimating flyable paths in complex environments.
APPLIED SOFT COMPUTING
(2023)
Article
Computer Science, Artificial Intelligence
Xiangyin Zhang, Shuang Xia, Xiuzhi Li, Tian Zhang
Summary: This paper proposes a multi-objective particle swarm optimization algorithm based on reinforcement learning (MCMOPSO-RL) to solve the collaborative path planning problem for multiple unmanned aerial vehicles (UAVs) in complex environments. The experimental results show that this algorithm can solve the path planning problem for multiple UAVs more efficiently and robustly.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Engineering, Marine
Liang Zhao, Yong Bai, Jeom Kee Paik
Summary: In this paper, a novel hierarchical motion planning framework is designed for unmanned surface vehicles (USVs) to respond to dynamic ocean environments. The framework includes global trajectory optimization and local reactive collision avoidance strategies, aiming to enhance adaptability to complex engineering problems. A adaptive-elite GA with fuzzy inference (AEGAfi) is proposed to solve the global optimization path planning problem, providing high-quality global paths. The framework also achieves COLREG-compliant local reaction by applying virtual sensory vector and softens the replanning time restriction by using a transition Clothoid path. The comprehensive simulations and comparisons demonstrate the effectiveness and superiority of the proposed framework in various ocean scenarios.
Article
Engineering, Aerospace
Xiangyin Zhang, Shuang Xia, Tian Zhang, Xiuzhi Li
Summary: This paper proposes an improved fireworks algorithm and particle swarm optimization cooperation algorithm for UAV global path planning. The algorithm is capable of generating high-quality solutions under multiple constraints and exhibits excellent performance in population diversity and global optimization capabilities.
AEROSPACE SCIENCE AND TECHNOLOGY
(2021)
Article
Computer Science, Hardware & Architecture
Yuan Tang, Yiming Miao, Ahmed Barnawi, Bander Alzahrani, Reem Alotaibi, Kai Hwang
Summary: This study proposes a joint global and local path planning optimization model for UAV task scheduling, utilizing various optimization algorithms and strategies to address the shortcomings of traditional surveillance equipment and UAV monitoring issues. Experiments show that the model has achieved good results in improving global and local path planning capabilities, further reducing path length, and successfully achieving the purpose of UAV task scheduling.
Article
Engineering, Ocean
Xiaoyuan Wang, Kai Feng, Gang Wang, Quanzheng Wang
Summary: The study proposes a local path optimization method for unmanned ships based on particle swarm acceleration calculation and dynamic optimal control, which utilizes a mathematical model and particle swarm optimization algorithm to optimize the local path in dynamic navigation environments.
APPLIED OCEAN RESEARCH
(2021)
Article
Multidisciplinary Sciences
Ziwei Wang, Guangkai Sun, Kangpeng Zhou, Lianqing Zhu
Summary: Unmanned Aerial Vehicle (UAV) path planning is improved by the proposed hybrid algorithm PESSA, which integrates particle swarm optimization (PSO) and enhanced sparrow search algorithm (ESSA). PESSA outperforms other algorithms in terms of average value and finds optimal values in 7 test functions. Furthermore, PESSA achieves better optimization results in 2D and 3D environments compared to other algorithms, demonstrating its feasibility and effectiveness.
Article
Engineering, Mechanical
Shuang Xia, Xiangyin Zhang
Summary: In this paper, a novel multi-objective particle swarm optimization algorithm (GMOPSO-QL) is proposed and applied to solve the constrained unmanned aerial vehicle (UAV) path planning problem. The simulation results show that GMOPSO-QL outperforms existing optimization algorithms in terms of efficiency and robustness.
Article
Computer Science, Artificial Intelligence
Manh Duong Phung, Quang Phuc Ha
Summary: This paper introduces a new algorithm named SPSO for UAV path planning, and demonstrates its superiority over other optimization algorithms in various scenarios through comparative experiments.
APPLIED SOFT COMPUTING
(2021)
Article
Computer Science, Information Systems
Zhenhua Yu, Zhijie Si, Xiaobo Li, Dan Wang, Houbing Song
Summary: This article proposes a novel hybrid particle swarm optimization (PSO) algorithm, SDPSO, for the automatic path planning problem of unmanned aerial vehicles (UAVs). The algorithm improves the update strategy of the global optimal solution in the PSO algorithm by merging the simulated annealing algorithm, and integrates the beneficial information of the optimal solution according to the dimensional learning strategy for each particle. Simulation results show that the SDPSO algorithm can quickly plan higher quality paths for UAVs and has better robustness in complex 3-D environments compared to other algorithms.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Automation & Control Systems
Yingjuan Jia, Liangdong Qu, Xiaoqin Li
Summary: This paper proposes a path planning method for unmanned combat aerial vehicles (UCAVs) in complex battlefield environments, which combines a double-layer coding model with the RPSO algorithm. The method reduces the number of superfluous points on the path and improves the exploration capacity of the PSO algorithm.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2022)
Article
Automation & Control Systems
Xiao-Jing Wu, Lei Xu, Ran Zhen, Xue-Li Wu
Summary: In this paper, three optimization strategies are proposed to enhance the search ability of the moth-flame optimization algorithm, including chaos-based moth initialization, adaptive weighted position update strategy, and population diversity improvement strategy. The chaos-based Logistic map is utilized in the moth initialization process to enhance population diversity. A nonlinear weighting factor is introduced in the spiral function to adaptively balance global and local search ability. Additionally, a new moth is generated using the population diversity improvement strategy, which enhances both diversity and optimality of the population. Simulation tests of UAV formation under multi-constraints demonstrate that the proposed global and local moth-flame optimization algorithm outperforms the latest path planning algorithms in terms of speed and optimality.
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS
(2023)
Article
Computer Science, Software Engineering
Yingxin Ma, Yuan Yao, Jinxiu Yang, Hang Zhang, Beishui Liao
Summary: This paper proposes a global continuous path planning method for 3D printing of Continuous fiber reinforced thermoplastic composites (CFRTPCs). It reduces complexity by optimizing print sequence, generating continuous Zigzag paths with controlled deposition direction, and avoiding interference.
COMPUTER-AIDED DESIGN
(2023)
Review
Computer Science, Artificial Intelligence
Alejandro Puente-Castro, Daniel Rivero, Alejandro Pazos, Enrique Fernandez-Blanco
Summary: Path planning problems with UAVs are well-studied, with applications in swarms speeding up flight time and reducing costs. The integration of AI algorithms allows for centralized control of multiple aircraft and optimal path computation. The review of recent literature shows an increasing trend in the use of AI techniques, indicating a shift in predominant methods.
NEURAL COMPUTING & APPLICATIONS
(2022)
Article
Chemistry, Analytical
Lisu Huo, Jianghan Zhu, Zhimeng Li, Manhao Ma
Summary: The study introduces a HDSOS algorithm that combines DE and SOS strategies, with both local and global search capabilities, as well as the introduction of traction function and perturbation strategy to enhance efficiency and robustness, comparative experiments demonstrate its superiority.
Review
Computer Science, Information Systems
Euclides Carlos Pinto Neto, Sajjad Dadkhah, Somayeh Sadeghi, Heather Molyneaux, Ali A. Ghorbani
Summary: The Internet of Things (IoT) has the potential to revolutionize medical treatment in healthcare, but it also faces security threats. Advanced analytics can enhance IoT security, but generating realistic datasets is complex. This research conducts a review of Machine Learning (ML) solutions for IoT security in healthcare, focusing on existing datasets, resources, applications, and challenges, to highlight the current landscape and future requirements.
COMPUTER COMMUNICATIONS
(2024)
Article
Computer Science, Information Systems
Duncan Deveaux, Takamasa Higuchi, Seyhan Ucar, Jerome Harri, Onur Altintas
Summary: This paper investigates the ability to predict the risk patterns of vehicles in a roundabout and suggests that constraining knowledge transfer to roundabouts with a similar context can significantly improve accuracy.
COMPUTER COMMUNICATIONS
(2024)
Article
Computer Science, Information Systems
Lingjun Zhao, Qinglin Yang, Huakun Huang, Longtao Guo, Shan Jiang
Summary: Metaverse seamlessly integrates the real and virtual worlds, and intelligent wireless sensing technology can serve as an intelligent, flexible, non-contact way to access the metaverse and accelerate the establishment of a bridge between the real physical world and the metaverse. However, there are still challenges and open issues in this field.
COMPUTER COMMUNICATIONS
(2024)
Article
Computer Science, Information Systems
Jing Xiong, Hong Zhu
Summary: With the rapid growth of data in the era of IoT, the challenge of data privacy protection arises. This article proposes a federated learning approach that uses collaborative training to obtain a global model without direct exposure to local datasets. By utilizing dynamic masking and adaptive differential privacy methods, the approach reduces communication overhead and improves the converge performance of the model.
COMPUTER COMMUNICATIONS
(2024)
Article
Computer Science, Information Systems
Carlos Rubio Garcia, Simon Rommel, Sofiane Takarabt, Juan Jose Vegas Olmos, Sylvain Guilley, Philippe Nguyen, Idelfonso Tafur Monroy
Summary: The reliance on asymmetric public key cryptography and symmetric encryption for cyber-security in current telecommunication networks is threatened by quantum computing technology. Quantum Key Distribution and post-quantum cryptography provide resistance to quantum attacks. This paper proposes two novel hybrid solutions integrating QKD and PQC into TLS for quantum-resistant key exchange.
COMPUTER COMMUNICATIONS
(2024)
Article
Computer Science, Information Systems
Annisa Sarah, Gianfranco Nencioni
Summary: This article explores the concept of a Slice Broker, an intermediate entity that purchases resources from Infrastructure Providers to offer customized network slices to users. The article proposes a cost-minimization problem and compares it with alternative problems to demonstrate its effectiveness and cost-saving capabilities.
COMPUTER COMMUNICATIONS
(2024)
Article
Computer Science, Information Systems
Sumana Maiti, Sudip Misra, Ayan Mondal
Summary: The broadcast proxy re-encryption methods extend traditional proxy re-encryption mechanisms and propose a scheme called MBP for IoT applications. MBP calculates a single re-encryption key for all user groups and uses multi-channel broadcast encryption to reduce security element size. However, it increases computation time for receiver IoT devices. The use of Rubinstein-Stahl bargaining game approach addresses this issue and MBP is secure against selective group chosen-ciphertext attack in the random oracle model.
COMPUTER COMMUNICATIONS
(2024)
Article
Computer Science, Information Systems
Pankaj Kumar, Hari Om
Summary: This paper presents NextGenV2V, a protocol for the next-generation vehicular network that achieves authenticated communication between vehicles using symmetric keys and a (2, n)-threshold scheme. The protocol reduces communication overhead and improves authentication delay, ensuring better security. Comparative analysis demonstrates the suitability of NextGenV2V in next-generation vehicular networks.
COMPUTER COMMUNICATIONS
(2024)
Article
Computer Science, Information Systems
Eric Ossongo, Moez Esseghir, Leila Merghem-Boulahia
Summary: The implementation of 5G networks allows for the efficient coexistence of heterogeneous services in a single physical virtualized infrastructure. Virtualization of network functions enables more flexible resource management and customizable services. However, the increasing number of connected objects poses challenges in managing physical and virtual resources, requiring intelligent systems to ensure communication quality.
COMPUTER COMMUNICATIONS
(2024)
Article
Computer Science, Information Systems
Suvrima Datta, U. Venkanna
Summary: The Internet of Things (IoT) enables real-time sensing and data transmission to make homes smarter. Effective device-type identification methods are crucial as the number of IoT devices continues to grow. In this paper, a P4-based gateway called PiGateway is proposed to classify and prioritize the type of IoT devices. By utilizing a decision tree model and flow rules, PiGateway enables real-time granular analysis and in-network classification of IoT traffic.
COMPUTER COMMUNICATIONS
(2024)
Article
Computer Science, Information Systems
Fahad Razaque Mughal, Jingsha He, Nafei Zhu, Saqib Hussain, Zulfiqar Ali Zardari, Ghulam Ali Mallah, Md. Jalil Piran, Fayaz Ali Dharejo
Summary: This paper explores the relationship between heterogeneous cluster networks and federated learning, as well as the challenges of implementing federated learning in heterogeneous networks and the Internet of Things. The authors propose an Intra-Clustered FL (ICFL) model that optimizes computation and communication to select heterogeneous FL nodes in each cluster, enabling efficient processing of asynchronous data and ensuring data security.
COMPUTER COMMUNICATIONS
(2024)
Article
Computer Science, Information Systems
Rajesh Kumar, Deepak Sinwar, Vijander Singh
Summary: This paper investigates the coexistence mechanisms between eMBB and URLLC traffic for resource scheduling in 5G. Through examining different approaches and performance metrics, it provides detailed insights for researchers in the field, and highlights key issues, challenges, and future directions.
COMPUTER COMMUNICATIONS
(2024)
Article
Computer Science, Information Systems
Giovanni Nardini, Giovanni Stea
Summary: Digital Twins of Networks (DTNs) are proposed as digital replicas of physical entities, enabling efficient data-driven network management and performance-driven network optimization. DTNs provide simulation services for dynamic reconfiguration and fault anticipation, using discrete-event network simulators as the ideal tools. Challenges include centralized vs. distributed implementation, input gathering from the physical network, security issues and hosting. The possibilities of network simulation for what-if analysis are explored, with the concepts of lockstep and branching analysis defined.
COMPUTER COMMUNICATIONS
(2024)
Article
Computer Science, Information Systems
Zhaolin Ma, Jiali You, Haojiang Deng
Summary: This paper presents the Distributed In-Network Name Resolution System (DINNRS), which leverages software-defined networking and Information-Centric Networking (ICN) paradigm to provide high scalability and minimal request delay. Our methods, including an enhanced marked cuckoo filter for fast resolving, achieve significant performance gains in simulation experiments.
COMPUTER COMMUNICATIONS
(2024)
Article
Computer Science, Information Systems
Yujie Wang, Ying Wang, Qingqing Liu, Yong Zhang
Summary: This paper proposes a dynamic indoor positioning method based on multi-scale metric learning of the channel state information (CSI). By constructing few-shot learning tasks, this method can achieve dynamic positioning using CSI signals without additional equipment. Experimental results show that compared to commonly used dynamic location and tracking algorithms, the proposed method has higher positioning accuracy and does not accumulate errors.
COMPUTER COMMUNICATIONS
(2024)
