-
Rigid Formation Control on a Sphere: A Heterogeneous System Approach IEEE Trans. Cybern. (IF 9.4) Pub Date : 2024-07-01 Sun-Ho Choi, Hyowon Seo
-
GraphMriNet: a few-shot brain tumor MRI image classification model based on Prewitt operator and graph isomorphic network Complex Intell. Syst. (IF 5.0) Pub Date : 2024-06-28 Bin Liao, Hangxu Zuo, Yang Yu, Yong Li
-
Recommending suitable hotels to travelers in the post-COVID-19 pandemic using a novel FAHP-fuzzy TOPSIS approach Complex Intell. Syst. (IF 5.0) Pub Date : 2024-06-27 Tin-Chih Toly Chen, Hsin-Chieh Wu, Keng-Wei Hsu
-
Resilient Output Control of Multiagent Systems With DoS Attacks and Actuator Faults: Fully Distributed Event-Triggered Approach IEEE Trans. Cybern. (IF 9.4) Pub Date : 2024-06-27 Juan Zhang, Dongsheng Yang, Weihua Li, Huaguang Zhang, Guangdi Li, Peng Gu
-
Robust Model Free Adaptive Predictive Control for Wastewater Treatment Process With Packet Dropouts IEEE Trans. Cybern. (IF 9.4) Pub Date : 2024-06-26 Hong-Gui Han, Shi-Jia Fu, Hao-Yuan Sun, Chen-Yang Wang
-
FedDBL: Communication and Data Efficient Federated Deep-Broad Learning for Histopathological Tissue Classification IEEE Trans. Cybern. (IF 9.4) Pub Date : 2024-06-26 Tianpeng Deng, Yanqi Huang, Guoqiang Han, Zhenwei Shi, Jiatai Lin, Qi Dou, Zaiyi Liu, Xiao-jing Guo, C. L. Philip Chen, Chu Han
-
Data-Driven Model Predictive Control for Redundant Manipulators With Unknown Model IEEE Trans. Cybern. (IF 9.4) Pub Date : 2024-06-25 Jingkun Yan, Long Jin, Bin Hu
-
Enhancing robustness in asynchronous feature tracking for event cameras through fusing frame steams Complex Intell. Syst. (IF 5.0) Pub Date : 2024-06-24 Haidong Xu, Shumei Yu, Shizhao Jin, Rongchuan Sun, Guodong Chen, Lining Sun
-
Multi-UAV pursuit-evasion gaming based on PSO-M3DDPG schemes Complex Intell. Syst. (IF 5.0) Pub Date : 2024-06-24 Yaozhong Zhang, Meiyan Ding, Jiandong Zhang, Qiming Yang, Guoqing Shi, Meiqu Lu, Frank Jiang
-
Enabling federated learning across the computing continuum: Systems, challenges and future directions Future Gener. Comput. Syst. (IF 6.2) Pub Date : 2024-06-24 Cédric Prigent, Alexandru Costan, Gabriel Antoniu, Loïc Cudennec
In recent years, as the boundaries of computing have expanded with the emergence of the Internet of Things (IoT) and its increasing number of devices continuously producing flows of data, it has become paramount to boost speed and to reduce latency. Recent approaches to this growing complexity and data deluge aim to integrate seamlessly and securely diverse computing tiers and data environments, spanning
-
Variational AdaBoost knowledge distillation for skin lesion classification in dermatology images Complex Intell. Syst. (IF 5.0) Pub Date : 2024-06-22 Xiangchun Yu, Guoliang Xiong, Jianqing Wu, Jian Zheng, Miaomiao Liang, Liujin Qiu, Lingjuan Yu, Qing Xu
-
DIB-UAP: enhancing the transferability of universal adversarial perturbation via deep information bottleneck Complex Intell. Syst. (IF 5.0) Pub Date : 2024-06-22 Yang Wang, Yunfei Zheng, Lei Chen, Zhen Yang, Tieyong Cao
-
Moboa: a proposal for multiple objective bean optimization algorithm Complex Intell. Syst. (IF 5.0) Pub Date : 2024-06-22 Lele Xie, Xiaoli Lu, Hang Liu, Yongqiang Hu, Xiaoming Zhang, Shangshang Yang
-
Complete area-coverage path planner for surface cleaning in hospital settings using mobile dual-arm robot and GBNN with heuristics Complex Intell. Syst. (IF 5.0) Pub Date : 2024-06-22 Ash Yaw Sang Wan, Lim Yi, Abdullah Aamir Hayat, Moo Chee Gen, Mohan Rajesh Elara
-
An adaptive trimming approach to Bayesian additive regression trees Complex Intell. Syst. (IF 5.0) Pub Date : 2024-06-22 Taoyun Cao, Jinran Wu, You-Gan Wang
-
Caching or not: An online cost optimization algorithm for geodistributed data analysis in cloud environments J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-22 Weitao Yang, Li Pan, Shijun Liu
With the wide application of big data technology, a large number of data geographically stored in data centers across various regions are generated everyday, waiting to be analyzed by big data tasks. Examples of such data analysis tasks include weather prediction and intelligent healthcare applications. Clouds are being used by more and more enterprises due to their nearly infinite resources, ease
-
Twin-tower transformer network for skeleton-based Parkinson’s disease early detection Complex Intell. Syst. (IF 5.0) Pub Date : 2024-06-21 Lan Ma, Hua Huo, Wei Liu, Changwei Zhao, Jinxuan Wang, Ningya Xu
-
SPSC: Stream Processing Framework Atop Serverless Computing for Industrial Big Data IEEE Trans. Cybern. (IF 9.4) Pub Date : 2024-06-21 Zinuo Cai, Zebin Chen, Xinglei Chen, Ruhui Ma, Haibing Guan, Rajkumar Buyya
-
MCTE-RPL: A multi-context trust-based efficient RPL for IoT J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-21 Javad Mohajerani, Mokhtar Mohammadi Ghanatghestani, Malihe Hashemipour
The Internet of things (IoT) is highly exposed to various attacks due to its sensitive applications, but it is very vulnerable in dealing with these attacks. So, various studies have been introduced to improve IoT security. Most of methods have focused on improving the security of the RPL protocol (Low-Power and Lossy Networks routing protocol) based on the development of trust models. However, most
-
Seraph: Towards secure and efficient multi-controller authentication with [formula omitted]-threshold signature in multi-domain SDWAN J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-21 Wendi Feng, Ke Liu, Shuo Sun, Bo Cheng, Wei Zhang
The multi-controller scheme is widely adopted in Software-Defined Wide Area Networks (SDWANs), where a WAN is segmented into multiple domains, each controlled by one controller. These controllers communicate with each other in-band, necessitating authentication before exchanging control messages. However, relying solely on identification of a single node for authentication exposes the network to spoofing
-
GRAAFE: GRaph Anomaly Anticipation Framework for Exascale HPC systems Future Gener. Comput. Syst. (IF 6.2) Pub Date : 2024-06-21 Martin Molan, Mohsen Seyedkazemi Ardebili, Junaid Ahmed Khan, Francesco Beneventi, Daniele Cesarini, Andrea Borghesi, Andrea Bartolini
The main limitation of applying predictive tools to large-scale supercomputers is the complexity of deploying Artificial Intelligence (AI) services in production and modeling heterogeneous data sources while preserving topological information in compact models. This paper proposes GRAAFE, a framework for continuously predicting compute node failures in the Marconi100 supercomputer. The framework consists
-
Scalable concept drift adaptation for stream data mining Complex Intell. Syst. (IF 5.0) Pub Date : 2024-06-20 Lisha Hu, Wenxiu Li, Yaru Lu, Chunyu Hu
-
DFFNet: a lightweight approach for efficient feature-optimized fusion in steel strip surface defect detection Complex Intell. Syst. (IF 5.0) Pub Date : 2024-06-20 Xianming Hu, Shouying Lin
-
CDT: Cross-interface Data Transfer scheme for bandwidth-efficient LoRa communications in energy harvesting multi-hop wireless networks J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-20 Hua Qin, Ni Li, Tao Wang, Gelan Yang, Yang Peng
With the capability of generating sustainable energy by exploiting the ambient environment (e.g., light, heat, vibrations, etc.), the energy harvesting (EH) technology is increasingly used on low-power smart objects, forming self-powered green Internet of Things (IoTs). Despite targeting different application domains, many of these green IoT systems adopt the distributed network paradigm by forming
-
Synthetic and privacy-preserving traffic trace generation using generative AI models for training Network Intrusion Detection Systems J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-20 Giuseppe Aceto, Fabio Giampaolo, Ciro Guida, Stefano Izzo, Antonio Pescapè, Francesco Piccialli, Edoardo Prezioso
-
Recent endeavors in machine learning-powered intrusion detection systems for the Internet of Things J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-20 D. Manivannan
The significant advancements in sensors and other resource-constrained devices, capable of collecting data and communicating wirelessly, are poised to revolutionize numerous industries through the Internet of Things (IoT). Sectors such as healthcare, energy, education, transportation, manufacturing, military, and agriculture stand to benefit. IoT is expected to play a crucial role in implementing both
-
A multi-UAV assisted task offloading and path optimization for mobile edge computing via multi-agent deep reinforcement learning J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-20 Tao Ju, Linjuan Li, Shuai Liu, Yu Zhang
To tackle task offloading and path planning challenges in multi-UAV-assisted mobile edge computing, this paper proposes a task offloading and path optimization approach via multi-agent deep reinforcement learning. The primary goal is to minimize the overall energy consumption of the system and improve computational performance. Initially, we established a model for a multi-UAV-assisted mobile edge
-
Blockchain empowered access control for digital twin system with attribute-based encryption Future Gener. Comput. Syst. (IF 6.2) Pub Date : 2024-06-20 Yueyue Dai, Jian Wu, Shuqi Mao, Xiaoyang Rao, Bruce Gu, Youyang Qu, Yunlong Lu
Digital twin is a pivotal and burgeoning technique that plays a crucial role in the realms of digital transformation and intelligent advancement. To bolster diverse applications and realize digital transformation, it is imperative to share the generated device data among multiple stakeholders involved in the digital twin system product life cycle. Since the device data contains sensitive and secret
-
Rapid screening of multi-point mutations for enzyme thermostability modification by utilizing computational tools Future Gener. Comput. Syst. (IF 6.2) Pub Date : 2024-06-20 Jia Jin, Qiaozhen Meng, Min Zeng, Guihua Duan, Ercheng Wang, Fei Guo
Enzymes play an important role in industry due to their catalytic properties and environmental friendliness. For application in harsh industrial environments, enzymes are modified to obtain improved stability through simultaneous mutations at multiple sites. Contrary to experimental methods, computational methods are significantly more efficient and cost-effective for screening stabilizing mutations
-
Decentralized IoT data sharing: A blockchain-based federated learning approach with joint optimizations for efficiency and privacy Future Gener. Comput. Syst. (IF 6.2) Pub Date : 2024-06-20 Ziwen Cheng, Yi Liu, Chao Wu, Yongqi Pan, Liushun Zhao, Xin Deng, Cheng Zhu
Blockchain-based Federated Learning (BCFL) is gaining significant attention as a promising decentralized data sharing technology with privacy protection. Most existing BCFL frameworks loosely couple blockchain and Federated Learning (FL). FL transforms data sharing into model sharing, while blockchain decentralizes the model aggregation and handles security verification. However, this simplistic overlay
-
Nested attention network based on category contexts learning for semantic segmentation Complex Intell. Syst. (IF 5.0) Pub Date : 2024-06-19 Tianping Li, Meilin Liu, Dongmei Wei
-
Synchronizing real-time and high-precision LDoS defense of learning model-based in AIoT with programmable data plane, SDN J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-19 Jie Ma, Wei Su, Yikun Li, Yuan Yuan, Ziqing Zhang
The availability of SD-AIoT is currently under complicated and serious cyber threats, especially Low-rate Denial-of-Service attacks. However, traditional defense schemes for such attacks with characteristics of high concealability and periodicity suffer from serious challenges with high detection difficulty, low accuracy of detection models, and inefficiency of mitigation approaches. In this paper
-
A hierarchical attention-based feature selection and fusion method for credit risk assessment Future Gener. Comput. Syst. (IF 6.2) Pub Date : 2024-06-19 Ximing Liu, Yayong Li, Cheng Dai, Hong Zhang
-
Multi-resource interleaving for task scheduling in cloud-edge system by deep reinforcement learning Future Gener. Comput. Syst. (IF 6.2) Pub Date : 2024-06-19 Xinglong Pei, Penghao Sun, Yuxiang Hu, Dan Li, Le Tian, Ziyong Li
Collaborative cloud–edge computing has been systematically developed to balance the efficiency and cost of computing tasks for many emerging technologies. To improve the overall performance of cloud–edge system, existing works have made progress in task scheduling by dynamically distributing the tasks with different latency thresholds to edge and cloud nodes. However, the relationship of multi-resource
-
Comprehensive comparisons of gradient-based multi-label adversarial attacks Complex Intell. Syst. (IF 5.0) Pub Date : 2024-06-18 Zhijian Chen, Wenjian Luo, Muhammad Luqman Naseem, Linghao Kong, Xiangkai Yang
Adversarial examples which mislead deep neural networks by adding well-crafted perturbations have become a major threat to classification models. Gradient-based white-box attack algorithms have been widely used to generate adversarial examples. However, most of them are designed for multi-class models, and only a few gradient-based adversarial attack algorithms specifically designed for multi-label
-
MDSTF: a multi-dimensional spatio-temporal feature fusion trajectory prediction model for autonomous driving Complex Intell. Syst. (IF 5.0) Pub Date : 2024-06-18 Xing Wang, Zixuan Wu, Biao Jin, Mingwei Lin, Fumin Zou, Lyuchao Liao
-
Enhancing honeynet-based protection with network slicing for massive Pre-6G IoT Smart Cities deployments J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-18 Antonio Matencio Escolar, Qi Wang, Jose Maria Alcaraz Calero
Internet of Things (IoT) coupled with 5G and upcoming pre-6G networks will provide the scalability and performance required to deploy a wide range of new digital services in Smart Cities. This new digital services will undoubtedly contribute to an improvement in the quality of life of citizens. However, security is a major concern in IoT where low-powered constrained devices are a target for attackers
-
GANFAT: Robust federated adversarial learning with label distribution skew Future Gener. Comput. Syst. (IF 6.2) Pub Date : 2024-06-18 Yayu Luo, Tongzhijun Zhu, Zediao Liu, Tenglong Mao, Ziyi Chen, Huan Pi, Ying Lin
As privacy concerns and regulatory constraints on data protection continue to grow, the distribution of collected data has become more dispersed, resembling a ”data silo” style. To harness these data effectively without exchanging raw data, federated learning has emerged as a prominent solution. However, distributions of user-generated data often exhibit imbalances between devices and labels, which
-
Transformer fusion-based scale-aware attention network for multispectral victim detection Complex Intell. Syst. (IF 5.0) Pub Date : 2024-06-16 Yunfan Chen, Yuting Li, Wenqi Zheng, Xiangkui Wan
-
Pose estimation algorithm based on point pair features using PointNet + + Complex Intell. Syst. (IF 5.0) Pub Date : 2024-06-16 Yifan Chen, Zhenjian Li, Qingdang Li, Mingyue Zhang
-
An edge-assisted group authentication scheme for the narrowband internet of things Complex Intell. Syst. (IF 5.0) Pub Date : 2024-06-16 Guosheng Zhao, Huan Chen, Jian Wang
-
Aggregation operators of complex fuzzy Z-number sets and their applications in multi-criteria decision making Complex Intell. Syst. (IF 5.0) Pub Date : 2024-06-16 Ali Köseoğlu, Fatma Altun, Rıdvan Şahin
-
Joint entity and relation extraction combined with multi-module feature information enhancement Complex Intell. Syst. (IF 5.0) Pub Date : 2024-06-16 Yao Li, He Yan, Ye Zhang, Xu Wang
-
Grounding rod hanging and removing robot with hand-eye self-calibration capability in substation Complex Intell. Syst. (IF 5.0) Pub Date : 2024-06-15 Yunhan Lin, Jiahui Wang, Kaibo Liu, Huasong Min
-
Joint data augmentations for automated graph contrastive learning and forecasting Complex Intell. Syst. (IF 5.0) Pub Date : 2024-06-15 Jiaqi Liu, Yifu Chen, Qianqian Ren, Yang Gao
-
An iterative two-phase optimization method for heterogeneous multi-drone routing problem considering differentiated demands Complex Intell. Syst. (IF 5.0) Pub Date : 2024-06-15 Huan Liu, Guohua Wu, Yufei Yuan, Dezhi Wang, Long Zheng, Wei Zhou
-
Enhancing learning on uncertain pixels in self-distillation for object segmentation Complex Intell. Syst. (IF 5.0) Pub Date : 2024-06-15 Lei Chen, Tieyong Cao, Yunfei Zheng, Yang Wang, Bo Zhang, Jibin Yang
-
Two-stage many-objective evolutionary algorithm: enhanced dominance relations and control mechanisms for separated balance Complex Intell. Syst. (IF 5.0) Pub Date : 2024-06-15 Wei Li, Qilin Niliang, Lei Wang, Qiaoyong Jiang
-
Hybrid structure of maximal ideals in near rings Complex Intell. Syst. (IF 5.0) Pub Date : 2024-06-15 B. Jebapresitha
-
Digital transformation with a lightweight on-premise PaaS Future Gener. Comput. Syst. (IF 6.2) Pub Date : 2024-06-15 Din Mušić, Jernej Hribar, Carolina Fortuna
The rise of cloud computing has been enabled by advances in virtualization and containerization technology. Over the past decade, the use of cloud computing has grown rapidly and has had a significant impact on digital transformation with many enterprises migrating to public clouds. While convenient and cost efficient, such approaches are prone to certain data privacy, compliance and security risks
-
Improving Hadoop MapReduce performance on heterogeneous single board computer clusters Future Gener. Comput. Syst. (IF 6.2) Pub Date : 2024-06-15 Sooyoung Lim, Dongchul Park
Over the past decade, Apache Hadoop has become a leading framework for big data processing. Single board computer (SBC) clusters, predominantly adopting Raspberry Pi (RPi), have been employed to explore the potential of MapReduce processing in terms of low power and cost because, capital costs aside, power consumption has also become a primary concern in many industries. After building SBC clusters
-
Research on charging strategy based on improved particle swarm optimization PID algorithm Complex Intell. Syst. (IF 5.0) Pub Date : 2024-06-14 Xiuzhuo Wang, Yanfeng Tang, Zeyao Li, Chunsheng Xu
-
Spatial-temporal memory enhanced multi-level attention network for origin-destination demand prediction Complex Intell. Syst. (IF 5.0) Pub Date : 2024-06-14 Jiawei Lu, Lin Pan, Qianqian Ren
-
Retraction Notice to “An Enhanced Consortium Blockchain Diversity Mining Technique for IoT Metadata Aggregation” [Future Generation Computer Systems 152 (2023) 239-253] / 7046 Future Gener. Comput. Syst. (IF 6.2) Pub Date : 2024-06-14 Premkumar Chithaluru, Fadi Al-Turjman, Raman Dugyala, Thompson Stephan, Manoj Kumar, Jagjit Singh Dhatterwal
-
Formal dependability analysis of fault tolerant Virtual Machine allocation strategies in Cloud Radio Access Network J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-13 Sana Younes, Maroua Idi
Cloud Radio Access Network (C-RAN) has been proposed as a fifth generation (5G) cellular network that is designed to physically separate the Baseband Units (BBUs) from the Remote Radio Heads (RRHs). The BBUs are placed in the BBU pool/hotel, while the RRHs are located in the cells. This separation enables sharing baseband processing resources among RRHs by generating Virtual Machines (VMs) in the BBU
-
Quantum-empowered federated learning and 6G wireless networks for IoT security: Concept, challenges and future directions Future Gener. Comput. Syst. (IF 6.2) Pub Date : 2024-06-13 Danish Javeed, Muhammad Shahid Saeed, Ijaz Ahmad, Muhammad Adil, Prabhat Kumar, A.K.M. Najmul Islam
The Internet of Things (IoT) has revolutionized various sectors by enabling seamless device interaction. However, the proliferation of IoT devices has also raised significant security and privacy concerns. Traditional security measures often fail to address these concerns due to the unique characteristics of IoT networks, such as heterogeneity, scalability, and resource constraints. This survey paper
-
Intelligent architecture and platforms for private edge cloud systems: A review Future Gener. Comput. Syst. (IF 6.2) Pub Date : 2024-06-13 Xiyuan Xu, Shaobo Zang, Muhammad Bilal, Xiaolong Xu, Wanchun Dou
The development of cloud, fog, and edge computing has led to great advances in reducing latency and saving bandwidth, and these methods have therefore been broadly applied in various domains, including healthcare, transportation, and the Internet of Things (IoT). Traditional edge computing solutions have proven to be insufficient in fulfilling the demanding prerequisites of low latency and high data
-
Web 3.0 security: Backdoor attacks in federated learning-based automatic speaker verification systems in the 6G era Future Gener. Comput. Syst. (IF 6.2) Pub Date : 2024-06-13 Yi Wu, Jiayi Chen, Tianbao Lei, Jiahua Yu, M. Shamim Hossain
With the advent of Next-Generation Web 3.0 and the integration of 6G technologies, digital industrial applications are undergoing unprecedented transformations. Among these, the field of intelligent voice recognition, particularly Federated Learning-based Automatic Speaker Verification (FL-ASV) systems, stands out by collaboratively training robust ASV models across systems while protecting sensitive
-
The Renoir Dataflow Platform: Efficient Data Processing without Complexity Future Gener. Comput. Syst. (IF 6.2) Pub Date : 2024-06-13 Luca De Martini, Alessandro Margara, Gianpaolo Cugola, Marco Donadoni, Edoardo Morassutto
Today, data analysis drives the decision-making process in virtually every human activity. This demands for software platforms that offer simple programming abstractions to express data analysis tasks and that can execute them in an efficient and scalable way. State-of-the-art solutions range from low-level programming primitives, which give control to the developer about communication and resource
-
An efficient scheduling scheme for intelligent driving tasks in a novel vehicle-edge architecture considering mobility and load balancing Future Gener. Comput. Syst. (IF 6.2) Pub Date : 2024-06-12 Nuanlai Wang, Shanchen Pang, Xiaofeng Ji, Haiyuan Gui, Xiao He
With the continuous popularization and evolution of 5G and 6G, mobile edge computing has achieved rapid development. This study explores the New Generation Mobile Edge Computing (NGMEC) architecture, which leverages numerous mobile nodes to provide users with enhanced computing services. Despite its advantages, NGMEC faces challenges such as high node mobility, load balancing difficulties, and incomplete