Future Internet, Volume 17, Issue 11

The digital age and the rise of Internet of Things technology have led to an explosion of data, including vast amounts of semantic data. In the context of large-scale semantic data graphs, centralized storage struggles to meet the efficiency requirem...

Programmable data planes are increasingly essential for enabling In-band Network Telemetry (INT), fine-grained monitoring, and congestion-aware packet processing. Although the P4 language provides a high-level abstraction to describe such behaviors,...

The rapid growth of the Internet of Things (IoT) has created vast networks of interconnected devices that are increasingly exposed to cyberattacks. Ensuring the security of such distributed systems requires efficient and adaptive intrusion detection...

Wind power plays an increasingly vital role in sustainable energy production, yet the harsh environments in which turbines operate often lead to mechanical or structural degradation. Detecting such faults early is essential to reducing maintenance ex...

Conversational text-to-SQL extends the traditional single-turn SQL generation paradigm to multi-turn, dialogue-based scenarios, enabling users to pose and refine database queries interactively, and requiring models to track dialogue context over mult...

This paper presents an analytical evaluation of three strategies designed to minimize service disruption during handovers in Software-Defined Networking (SDN)-based connected car networks: SDN Mobility with a Caching Policy, cache-miss Content Delive...

The composition of cloud services plays a vital role in optimizing resource allocation, load balancing, task scheduling, and energy management. However, it remains a significant challenge due to the dynamic nature of workloads and the variability in...

In the evolving landscape of Mobile Crowdsourcing (MCS), ensuring the security and privacy of both stored and transmitted multimedia content has become increasingly challenging. Factors such as human mobility, device heterogeneity, dynamic topologies...

Network digital twins (NDTs) are emerging as key enablers of 6G networks integrating artificial Intelligence (AI) techniques. NDT systems offer novel features, including real-time monitoring, simulation, enhanced network planning, autonomous manageme...

Hand rehabilitation requires consistent, repetitive exercises that can often reduce patient motivation, especially in home-based therapy. This study introduces ReHAb Playground, a deep learning-based system that merges real-time gesture recognition w...

Resilient autonomous inter-Unmanned Aerial Vehicle (UAV) communication is critical for applications like drone swarms. While conventional Global Navigation Satellite System (GNSS)-based beamforming is effective at long ranges, it suffers from signifi...

Wireless Sensor Networks (WSNs) have a decisive share in various monitoring and control systems. However, their distributed and resource-constrained nature makes them vulnerable to anomalies caused by factors such as environmental noise, sensor fault...

Scheduling computing is a well-studied area focused on improving task execution by reducing processing time and increasing system efficiency. Divisible Load Theory (DLT) provides a structured analytical framework for distributing partitionable comput...

Predicting the behavior of Internet of Things (IoT) networks under irregular topologies and heterogeneous battery conditions remains a significant challenge. Simulation tools can capture these effects but can require high manual effort and computatio...

Generative models can generate art within a single modality with high fidelity. However, translating a work of art from one domain to another (e.g., painting to music or poem to painting) in a meaningful way remains a longstanding, interdisciplinary...

The rapid expansion of satellite networks for advanced communication and space exploration has ensured that robust cybersecurity for inter-satellite links has become a critical challenge. Traditional security models rely on centralized trust authorit...

The new availability of powerful Artificial Intelligence (AI) as an everyday copilot has instigated a new wave of attack techniques, especially in the area of Social Engineering (SE). The possibility of generating a multitude of different templates w...

The utilization of high millimeter wave (mmWave, 30–100 GHz) in 5G New Radio (NR) systems and sub-terahertz (sub-THz, 100–300 GHz) in future 6G requires dense deployments of base stations (BSs) to provide uninterrupted connectivity to the...

The rapid evolution of cyber threats requires intelligence sharing between organizations while ensuring data privacy and contributor credibility. Existing centralized cyber threat intelligence (CTI) systems suffer from single points of failure, priva...

The use of Artificial Intelligence (AI) in healthcare has significantly advanced early disease detection, enabling timely diagnosis and improved patient outcomes. This work proposes an end-to-end machine learning (ML) model for predicting diabetes ba...

With the rapid adoption of generative AI technologies across various sectors, it has become increasingly important to understand how these systems handle personal data. The study examines users’ awareness of the types of data collected, the ris...

Cultural heritage conservation faces escalating challenges from environmental threats and resource constraints, necessitating innovative preservation strategies that balance predictive accuracy with interpretability. This study presents a hybrid neur...

Speech Emotion Recognition (SER) is important for applications such as Human–Computer Interaction (HCI) and emotion-aware services. Traditional SER models rely on utterance-level labels, aggregating frame-level representations through pooling o...

The aviation industry operates as a complex, dynamic system generating vast volumes of data from aircraft sensors, flight schedules, and external sources. Managing this data is critical for mitigating disruptive and costly events such as mechanical f...

NISQ (Noisy Intermediate-Scale Quantum) era constraints, high sensitivity to noise and limited qubit count, impose significant barriers on the usability of QPUs (Quantum Process Units) capabilities. To overcome these challenges, researchers are explo...

Efficient and secure inter-task communication (ITC) is critical in real-time embedded systems, particularly in security-sensitive architectures. Traditional ITC mechanisms in Real-Time Operating Systems (RTOSs) often incur high latency from kernel tr...

Federated learning (FL) is a foundational technology for enabling collaborative intelligence in vehicular edge computing (VEC). However, the volatile network topology caused by high vehicle mobility and the profound security risks of model poisoning...

In data visualization, users’ scanning patterns are as crucial as their reading patterns in text-based media. Yet, no systematic attempt exists to characterize this activity with basic features, such as reading speed and scanpaths, nor to relat...

Over the last decade, Software-Defined Networking (SDN) has garnered increasing research interest for networking and security. This interest stems from the programmability and dynamicity offered by SDN, as well as the growing importance of SDN as a f...

This paper introduces a novel framework that integrates reinforcement learning with declarative modeling and mathematical optimization for dynamic resource allocation during mass casualty incidents. Our approach leverages Mesa as an agent-based model...

We developed a machine vision-based robotic system to address automation challenges in pharmaceutical pill sorting and packaging. The hardware platform integrates a high-resolution industrial camera with an HSR-CR605 robotic arm. Image processing lev...

This work presents and evaluates two threshold-based detection methods for the Six-State quantum key distribution protocol, considering a realistic scenario involving partial intercept–resend attack and channel noise. The statistical properties...

Traditional cyber attack-defense strategies have traditionally focused solely on the attacker and defender, while neglecting the role of government-led system administrators. To address strategic selection challenges in cyber warfare, this study empl...

This paper proposes an efficient sparse channel estimation method for millimeter wave (mmWave) hybrid multiple-input multiple-output (MIMO) systems. The performance of orthogonal matching pursuit (OMP) and its advanced variants—generalized OMP...

Dynamic and efficient resource allocation is critical for Software-Defined Networking (SDN) enabled sixth-generation (6G) networks to ensure adaptability and optimized utilization of network resources. This paper proposes a reinforcement learning (RL...

Modular monolithic architecture (MMA) has recently emerged as a hybrid architecture that is positioned between traditional monoliths and microservices. It combines operational simplicity with modularity and maintainability. Although industry adoption...

Lung cancer (LC) remains a leading cause of cancer mortality worldwide, where accurate and early identification of gene mutations such as epidermal growth factor receptor (EGFR) is critical for precision treatment. However, machine learning-based rad...

Tactile Internet (TI) is an innovative paradigm for emerging generations of communication systems that support ultra-low latency and highly robust transmission of haptics, actuation, and immersive communication in real time. It is considered a critic...

Industrial Internet of Things (IIoT) systems face severe security and trust challenges, particularly under cross-domain data sharing and federated orchestration. We present QuantumTrust-FedChain, a cyber-resilient federated learning framework integra...

The rapid proliferation of devices on the Internet of Things (IoT) in smart city environments enables autonomous decision-making, but introduces challenges of scalability, coordination, and privacy. Existing reinforcement learning (RL) methods, such...

This article examines the role of fairness in software across diverse application contexts, with a particular emphasis on healthcare, and introduces the concept of algorithmic (individual) meta-fairness. We argue that attaining a high degree of fairn...

The integration of artificial intelligence (AI) and edge computing gives rise to edge intelligence (EI), which offers effective solutions to the limitations of traditional cloud-based AI; however, deploying models across distributed edge platforms ra...

Image classification is central to computer vision, supporting applications from autonomous driving to medical imaging, yet state-of-the-art convolutional neural networks remain constrained by heavy floating-point operations (FLOPs) and parameter cou...

This paper introduces TRIDENT-DE, a novel ensemble-based variant of Differential Evolution (DE) designed to tackle complex continuous global optimization problems. The algorithm leverages three complementary trial vector generation strategies best/1/...

In response to the persistent failures of traditional election polling, this study introduces the Decentralized Prediction Market Voter Framework (DPMVF), a novel tool to empirically test and quantify the predictive capabilities of Decentralized Pred...

Generally, the interpretability of deep neural networks is categorized into a priori and a posteriori interpretability. A priori interpretability involves improving model transparency through deliberate design prior to training. Feature disentangleme...

Private fifth generation (5G) networks have emerged as a cornerstone for ultra-reliable, low-latency connectivity across mission-critical domains such as industrial automation, healthcare, and smart cities. Compared to conventional technologies like...

Service Function Chain (SFC) is a framework that dynamically orchestrates Virtual Network Functions (VNFs) and is essential to enhancing resource scheduling efficiency. However, traditional scheduling methods face several limitations, such as low mat...

Container-based virtualization has become pivotal in cloud computing, and resource fragmentation is inevitable due to the frequency of container deployment/termination and the heterogeneous nature of IoT tasks. In queuing cloud systems, resource defr...

The transition to 5G networks brings unprecedented speed, ultra-low latency, and massive connectivity. Nevertheless, it introduces complex traffic patterns and broader attack surfaces that render traditional intrusion detection systems (IDSs) ineffec...