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Optimization of datacenter selection through a genetic algorithm-driven service broker policy
Establishing an optimal datacenter selection policy within the cloud environment is paramount to maximize the performance of the cloud services. Service broker policy governs the selection of datacenters for u...
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Building integrated assessment model for IoT technology deployment in the Industry 4.0
Internet of Things (IoT) platforms have become the building blocks of any automated system but they are more important in case of industrial systems where sensitive data are captured and handled by the informa...
Privacy-enhanced distributed revocable identity management scheme based self-sovereign identity
In recent years, the rapid proliferation of digital services and resources on Industrial Internet has imposed higher demands on universality and privacy of identity management. Particularly with the advent of ...
COPSA: a computation offloading strategy based on PPO algorithm and self-attention mechanism in MEC-empowered smart factories
With the dawn of Industry 5.0 upon us, the smart factory emerges as a pivotal element, playing a crucial role in the realm of intelligent manufacturing. Meanwhile, mobile edge computing is proposed to alleviat...
Multi-agent Deep Reinforcement Learning for cloud-based digital twins in power grid management
As the power industry becomes increasingly complex, Digital Twin (DT) technology has emerged as a crucial tool for enhancing grid resilience and operational efficiency by creating dynamic digital replicas of p...
I-MPaFS: enhancing EDoS attack detection in cloud computing through a data-driven approach
Cloud computing offers cost-effective IT solutions but is susceptible to security threats, particularly the Economic Denial of Sustainability (EDoS) attack. EDoS exploits cloud elasticity and the pay-per-use b...
Explainable AI-based innovative hybrid ensemble model for intrusion detection
Cybersecurity threats have become more worldly, demanding advanced detection mechanisms with the exponential growth in digital data and network services. Intrusion Detection Systems (IDSs) are crucial in ident...
PPDNN-CRP: privacy-preserving deep neural network processing for credit risk prediction in cloud: a homomorphic encryption-based approach
This study proposes a Privacy-Preserving Deep Neural Network for Credit Risk Prediction (PPDNN-CRP) framework that leverages homomorphic encryption (HE) to ensure data privacy throughout the credit risk predic...
BGFL: a blockchain-enabled group federated learning at wireless industrial edges
In the rapidly evolving landscape of Industry 4.0, the complex computational tasks and the associated massive data volumes present substantial opportunities for advancements in machine learning at industry edg...
Cost modelling and optimisation for cloud: a graph-based approach
Cloud computing has become popular among individuals and enterprises due to its convenience, scalability, and flexibility. However, a major concern for many cloud service users is the rising cost of cloud reso...
A systematic review on blockchain-based access control systems in cloud environment
The widespread adoption of cloud computing has dramatically altered how data is stored, processed, and accessed in an era. The rapid development of digital technologies characterizes all this. The widespread a...
Optimization model for vehicular network data queries in edge environments
As the Internet of Vehicles advances, the demand for timely data acquisition by vehicle users continues to escalate, albeit confronted with the challenge of excessive data retrieval latency. The emergence of e...
A multi-strategy ontology mapping method based on cost-sensitive SVM
As the core of ontology integration, the task of ontology mapping is to find the semantic relationship between ontologies. Nevertheless, most existing ontology mapping methods only rely ontext information to c...
Domain knowledge free cloud-IDS with lightweight embedding method
The expansion of the cloud computing market has provided a breakthrough in efficiently storing and managing data for individuals and companies. As personal and corporate data move to the cloud, diverse attacks...
Pain assessment from facial expression images utilizing Statistical Frei-Chen Mask (SFCM)-based features and DenseNet
Estimating pain levels is crucial for patients with serious illnesses, those recovering from brain surgery, and those receiving intensive care etc. An automatic pain intensity estimator is proposed in this stu...
A cost-efficient content distribution optimization model for fog-based content delivery networks
The massive data demand requires content distribution networks (CDNs) to use evolving techniques for efficient content distribution with guaranteed quality of service (QoS). The distributed fog-based CDN model...
Toward security quantification of serverless computing
Serverless computing is one of the recent compelling paradigms in cloud computing. Serverless computing can quickly run user applications and services regardless of the underlying server architecture. Despite ...
SMedIR: secure medical image retrieval framework with ConvNeXt-based indexing and searchable encryption in the cloud
The security and privacy of medical images are crucial due to their sensitive nature and the potential for severe consequences from unauthorized modifications, including data breaches and inaccurate diagnoses....
A trusted IoT data sharing method based on secure multi-party computation
Edge computing nodes close to the perception layer of IoT systems are susceptible to data leaks and unauthorized access. To address these security concerns, this paper proposes a trusted IoT data sharing metho...
Wind power prediction method based on cloud computing and data privacy protection
With the support of our government’s commitment to the energy sector, the installed capacity of wind power will continue to grow. However, due to the instability of wind power, accurate prediction of wind powe...
Dependency-aware online task offloading based on deep reinforcement learning for IoV
The convergence of artificial intelligence and in-vehicle wireless communication technologies, promises to fulfill the pressing communication needs of the Internet of Vehicles (IoV) while promoting the develop...
Using blockchain and AI technologies for sustainable, biodiverse, and transparent fisheries of the future
This paper proposes a total fusion of blockchain and AI tech for tomorrow’s viable, rich in diversity and transparent fisheries. It outlines the main goal of tackling overfishing challenges due to lack of tran...
Predictive digital twin driven trust model for cloud service providers with Fuzzy inferred trust score calculation
Cloud computing has become integral to modern computing infrastructure, offering scalability, flexibility, and cost-effectiveness. Trust is a critical aspect of cloud computing, influencing user decisions in s...
When wavelet decomposition meets external attention: a lightweight cloud server load prediction model
Load prediction tasks aim to predict the dynamic trend of future load based on historical performance sequences, which are crucial for cloud platforms to make timely and reasonable task scheduling. However, ex...
Compliance and feedback based model to measure cloud trustworthiness for hosting digital twins
Cloud-based digital twins use real-time data from various data sources to simulate the behavior and performance of their physical counterparts, enabling monitoring and analysis. However, one restraining factor...
Human digital twin: a survey
The concept of the Human Digital Twin (HDT) has recently emerged as a new research area within the domain of digital twin technology. HDT refers to the replica of a physical-world human in the digital world. C...
Deep learning based enhanced secure emergency video streaming approach by leveraging blockchain technology for Vehicular AdHoc 5G Networks
VANET is a category of MANET that aims to provide wireless communication. It increases the safety of roads and passengers. Millions of people lose their precious lives in accidents yearly, millions are injured...
SSF-CDW: achieving scalable, secure, and fast OLAP query for encrypted cloud data warehouse
Implementing a cloud-based data warehouse to store sensitive or critical strategic data presents challenges primarily related to the security of the stored information and the exchange of OLAP queries between ...
Energy-aware tasks offloading based on DQN in medical mobile devices
Offloading some tasks from the local device to the remote cloud is one of the important methods to overcome the drawbacks of the medical mobile device, such as the limitation in the execution time and energy s...
Adaptive heuristic edge assisted fog computing design for healthcare data optimization
Patient care, research, and decision-making are all aided by real-time medical data analysis in today’s rapidly developing healthcare system. The significance of this research comes in the fact that it has the...
Optimizing energy efficiency in MEC networks: a deep learning approach with Cybertwin-driven resource allocation
Cybertwin (CT) is an innovative network structure that digitally simulates humans and items in a virtual environment, significantly influencing Cybertwin instances more than regular VMs. Cybertwin-driven netwo...
Attack detection model for BCoT based on contrastive variational autoencoder and metric learning
With development of blockchain technology, clouding computing and Internet of Things (IoT), blockchain and cloud of things (BCoT) has become development tendency. But the security has become the most developme...
MDB-KCP: persistence framework of in-memory database with CRIU-based container checkpoint in Kubernetes
As the demand for container technology and platforms increases due to the efficiency of IT resources, various workloads are being containerized. Although there are efforts to integrate various workloads into K...
Enhancing intrusion detection: a hybrid machine and deep learning approach
The volume of data transferred across communication infrastructures has recently increased due to technological advancements in cloud computing, the Internet of Things (IoT), and automobile networks. The netwo...
An intelligent decision system for virtual machine migration based on specific Q-learning
Due to the convenience of virtualization, the live migration of virtual machines is widely used to fulfill optimization objectives in cloud/edge computing. However, live migration may lead to side effects and ...
Real-time scheduling of power grid digital twin tasks in cloud via deep reinforcement learning
As energy demand continues to grow, it is crucial to integrate advanced technologies into power grids for better reliability and efficiency. Digital Twin (DT) technology plays a key role in this by using data ...
ASOD: an adaptive stream outlier detection method using online strategy
In the current era of information technology, blockchain is widely used in various fields, and the monitoring of the security and status of the blockchain system is of great concern. Online anomaly detection f...
Computational intelligence-based classification system for the diagnosis of memory impairment in psychoactive substance users
Computational intelligence techniques have emerged as a promising approach for diagnosing various medical conditions, including memory impairment. Increased abuse of psychoactive drugs poses a global public he...
Adaptive scheduling-based fine-grained greybox fuzzing for cloud-native applications
Coverage-guided fuzzing is one of the most popular approaches to detect bugs in programs. Existing work has shown that coverage metrics are a crucial factor in guiding fuzzing exploration of targets. A fine-gr...
Non-orthogonal multiple access-based MEC for energy-efficient task offloading in e-commerce systems
Mobile edge computing (MEC) reduces the latency for end users to access applications deployed at the edge by offloading tasks to the edge. With the popularity of e-commerce and the expansion of business scale,...
Multiple time servers timed-release encryption based on Shamir secret sharing for EHR cloud system
Electronic health record (EHR) cloud system, as a primary tool driving the informatization of medical data, have positively impacted both doctors and patients by providing accurate and complete patient informa...
Efficiently localizing system anomalies for cloud infrastructures: a novel Dynamic Graph Transformer based Parallel Framework
Cloud environment is a virtual, online, and distributed computing environment that provides users with large-scale services. And cloud monitoring plays an integral role in protecting infrastructures in the clo...
From data to insights: the application and challenges of knowledge graphs in intelligent audit
In recent years, knowledge graph technology has been widely applied in various fields such as intelligent auditing, urban transportation planning, legal research, and financial analysis. In traditional auditin...
HybOff: a Hybrid Offloading approach to improve load balancing in fog environments
Load balancing is crucial in distributed systems like fog computing, where efficiency is paramount. Offloading with different approaches is the key to balancing the load in distributed environments. Static off...
Hierarchical Identity-Based Authenticated Encryption with Keyword Search over encrypted cloud data
With the rapid development of cloud computing technology, cloud storage services are becoming more and more mature. However, the storage of sensitive data on remote servers poses privacy risks and is presently...
Correction to: Enhancing lung cancer diagnosis with data fusion and mobile edge computing using DenseNet and CNN
The original article was published in Journal of Cloud Computing 2024 13 :91
ABWOA: adaptive boundary whale optimization algorithm for large-scale digital twin network construction
Digital twin network (DTN) as an emerging network paradigm, have garnered growing attention. For large-scale networks, a crucial problem is how to effectively map physical networks onto the infrastructure plat...
Distance optimization and directional overcurrent relay coordination using edge-powered biogeography-genetic algorithms
The effective functioning and regulation of power systems crucially rely on the coordination of distance and directional overcurrent relays. Accurate fault detection and successful clearing sequences require s...
Towards optimized scheduling and allocation of heterogeneous resource via graph-enhanced EPSO algorithm
Efficient allocation of tasks and resources is crucial for the performance of heterogeneous cloud computing platforms. To achieve harmony between task completion time, device power consumption, and load balanc...
Topic and knowledge-enhanced modeling for edge-enabled IoT user identity linkage across social networks
The Internet of Things (IoT) devices spawn growing diverse social platforms and online data at the network edge, propelling the development of cross-platform applications. To integrate cross-platform data, use...
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Citation Impact 2023 Journal Impact Factor: 3.7 5-year Journal Impact Factor: 3.8 Source Normalized Impact per Paper (SNIP): 1.406 SCImago Journal Rank (SJR): 0.995
Speed 2023 Submission to first editorial decision (median days): 12 Submission to acceptance (median days): 116
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