The restricted coverage of edge servers in the Internet of Vehicles (IoV) results in service migration as vehicles traverse various regions, potentially escalating operational costs and diminishing service quality. However, existing service ...

Sparse Mobile Crowdsensing (SMCS) provides vital support for wide-range urban sensing by collecting data from only a few sub-regions and inferring data of unperceived sub-regions based on the spatiotemporal relationships of the collected data. ...

The sixth-generation (6G) of wireless networks is expected to surpass its predecessors by offering ubiquitous coverage of sensing, communication, and computing by the deployment of space-air-ground integrated networks (SAGINs). In SAGINs, aerial ...

Application placement in Multi-Access Edge Computing (MEC) must adhere to service level agreements (SLAs), minimize energy consumption, and optimize metrics based on specific service requirements. In distributed MEC system environments, the ...

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• Distributed Deep Reinforcement Learning based Capacity-Aware Application Placement.
• Reduction of the number of active edge nodes and compliance with SLA.
• Vertical application deployment impact on the application placement approach.

Vehicle-to-vehicle (V2V) communication is a critical technology in supporting vehicle safety applications in vehicular networks. The high mobility in vehicular networks makes the channel state change rapidly, which poses significant challenges to ...

Consider an infrastructure-less wireless network environment (e.g., a land battlefield) in which devices are characterized by varying resource configurations, dynamic mobility, complexity of the generated sensing tasks, and deterministic delay ...

Fueled by the popularity of mobile devices, mobile channels have become the preferred video delivery medium. However, users often encounter a poor quality of experience (QoE) due to bandwidth limitations, despite the implementation of adaptive ...

Federated learning (FL) is an increasingly popular privacy-preserving collaborative machine learning paradigm that enables clients to train a global model collaboratively without sharing their raw data. Despite its advantages, FL is vulnerable to ...

This study focuses on cooperative beamforming among base stations in wireless communication technology and proposes a new approach based on the Free Energy Principle (FEP). Traditionally, the trade-off between the accuracy of channel information ...

In the industrial internet of things, the rapid development of smart mobile devices and 5G network technology has driven the application of mobile edge computing, reducing the delay in task computation offloading to some extent. However, the ...

• We utilized Voronoi diagrams to divide service management areas of edge servers, improving offloading efficiency.
• We developed a PCA-based offloading security evaluation model (PCA-OSEM) to analyze key factors affecting offloading ...

Computer simulation platforms offer an alternative solution by emulating complex systems in a controlled manner. However, existing Edge Computing (EC) simulators, as well as general-purpose vehicular network simulators, are not tailored for VEC ...

• Vehicular edge network modeling establish foundation for simulator design
• Modular architecture and rich APIs enable flexible simulator customization
• Realistic-enhanced mechanisms replicate heterogeneous access patterns
• In-depth ...

Encrypted traffic detection and classification is a critical domain in network security, increasingly essential in an era of pervasive encryption. This survey paper delves into integrating advanced Machine Learning (ML) and Deep Learning (DL) ...

• Taxonomy of Encrypted Traffic Detection and Classification Models.
• Survey of Techniques for Encrypted Traffic Detection and Classification.
• Comprehensive Analysis of Datasets.
• Overview of Technical Analyzers/Information ...

Vehicular crowdsensing leverages the mobility and sensing capabilities of vehicles to provide efficient data collection and monitoring services for urban areas. However, maintaining data freshness in urban sensing environments while addressing ...

Encrypted traffic classification plays a critical role in network traffic management and optimization, as it helps identify and differentiate between various types of traffic, thereby enhancing the quality and efficiency of network services. ...

The rapid development of reconfigurable intelligent surfaces (RISs) has sparked transformative advancements in wireless communication systems. These intelligent metasurfaces, adept at dynamically manipulating electromagnetic (EM) waves, hold vast ...

Reconfigurable intelligent surface (RIS) is expected to be able to significantly reduce task processing delay and energy consumptions of mobile users (MUs) in mobile edge computing (MEC) by intelligently adjusting its reflecting elements’ phase-...

The volume and diversity of Internet traffic are constantly growing due to the simplicity of Internet of Things (IoT) technology, making machine learning-powered solutions increasingly essential for efficient network oversight in the future. The ...

• We proposed the cost sensitive XGBoost algorithm for multi-class classification.
• To overcome the minority class data an active learning framework is implemented.
• we employed the uncertainty sampling technique to decrease the ...

Internet of Things (IoT) devices are often used as springboards for network intrusion due to the open nature of IoT protocol stacks that enable automatic inter-connection and data sharing among devices, so it is critical to develop network ...

High-stakes process industries require a harmonious relationship between the Safety Instrumented System (SIS) and the Basic Process Control System (BPCS) to guarantee the safety and stability of operations. As security threats to SIS intensify, ...

• Propose SFACIF to identify safety function attacks and anomaly industrial conditions.
• Propose a coding scheme to differentiate safety function attack from industrial anomalies.
• Propose a modified SWRSM to address the higher fault ...

Understanding group information and collective behaviors is an ongoing area of research, encompassing natural phenomena and human dynamics. Quantifying interactions and interdependencies at the group level can be valuable for understanding ...

• Investigation of multiple Autonomous Systems (ASes) in terms of group information and dynamics for the purposes of group-AS level BGP anomaly detection.
• The first time Multidimensional Recurrence Quantification Analysis (MdRQA) has ...