Future Internet, Volume 17, Issue 9

Accurate livestock monitoring is critical for precision agriculture, supporting effective farm management, disease prevention, and sustainable resource allocation. Deep learning and remote sensing are recent technological advancements that have creat...

This study investigates how AI-driven innovations are reshaping manufacturing value chains through the transition from Industry 4.0 to Industry 6.0, particularly in resource-intensive sectors such as ceramics. Addressing a gap in the literature, the...

This work proposes a behavior-aware caching architecture that improves cache hit rates by up to 10.8% over LRU and 36% over LFU in large-scale web applications, reducing redundant traffic and alleviating backend server load. The architecture partitio...

This study examines the evolution and impact of Big Data technologies across sectors, emphasizing key algorithms, emerging trends, and organizational challenges in their adoption. Special attention is given to ethical concerns related to data privacy...

In this study, we investigate a deep learning-based vehicle fault prediction model aimed at achieving accurate prediction of vehicle faults by analyzing the correlations among different faults and the impact of critical faults on future fault develop...

Real-time media streaming over publish–subscribe platforms is increasingly vital in scenarios that demand the scalability of event-driven architectures while ensuring timely media delivery. This is especially true in multi-modal and resource-co...

Smart meters (SMs) are essential components of modern smart grids, enabling real-time and accurate monitoring of electricity consumption. However, their evaluation is often hindered by proprietary communication protocols and the high cost of commerci...

The rapid expansion of cyber-physical systems (CPSs) and networked environments—including the Internet of Things (IoT), Industrial IoT (IIoT), and the Internet of Vehicles (IoV)—has transformed modern infrastructures, enabling unprecedent...

Content caching and exchange through device-to-device (D2D) communications can offload data from the centralized base station and improve the quality of users’ experience. However, existing studies often overlook the selfish nature of user equi...

The rapid development of an increasing volume of web apps and the improper testing of the resulting code invariably provide more attack surfaces to potentially exploit. This leads to higher chances of facing cybersecurity breaches that can negatively...

Meeting global forest restoration targets by 2030 requires a transition from labor-intensive and opaque practices to scalable, intelligent, and verifiable systems. This paper introduces a cyber–physical digital twin architecture for forest rest...

In an attempt to improve utilization of the frequency spectrum left vacant by license holders, cognitive radio networks (CRNs) permit secondary users (SUs) to utilize such spectrum when the license holders, known as primary users (PUs), are inactive....

The rapid adoption of Metaverse technologies in healthcare, particularly for elder safety monitoring, has introduced new security challenges related to the authenticity of virtual representations. As healthcare providers increasingly rely on avatars...

Java 8 brought functional programming to the Java language and library, enabling more expressive and concise code to replace loops by using streams. Despite such advantages, for-loops remain prevalent in current codebases as the transition to the fun...

Intelligent edge machine learning has emerged as a paradigm for deploying smart applications across resource-constrained devices in next-generation network infrastructures. This survey addresses the critical challenges of implementing machine learnin...

As smart cities evolve, the demand for real-time, secure, and adaptive network monitoring, continues to grow. Software-Defined Networking (SDN) offers a centralized approach to managing network flows; However, anomaly detection within SDN environment...

Background: Container orchestration systems like Kubernetes rely heavily on declarative manifest files, which serve as orchestration blueprints. However, managing these manifest files is often complex and requires substantial DevOps expertise. Method...

The proliferation of sensor technology has led to an explosion in data volume, making the retrieval of specific information from large repositories increasingly challenging. While Retrieval-Augmented Generation (RAG) can enhance Large Language Models...

This study presents a deep generative model designed to predict intermediate stages in the drawing process of character illustrations. To enhance generalization and robustness, the model integrates a variational bottleneck based on the Variational Au...

Large language models (LLMs) have advanced rapidly as tools for automating code generation in scientific research, yet their ability to interpret and use unfamiliar Python APIs for complex computational experiments remains poorly characterized. This...

Distributed denial-of-service (DDoS) attacks are a prevalent threat to resource-constrained IoT deployments. We present an edge-based detection and mitigation system integrated with the oneM2M architecture. By using a Raspberry Pi 4 client and five R...

As the demand for high-quality video streaming applications continues to rise, multi-access edge computing (MEC)-assisted streaming schemes have emerged as a viable solution within the context of HTTP adaptive streaming (HAS). These schemes aim to en...

The Industrial Internet of Things (IIoT) is transforming industrial operations through connected devices and real-time automation but also introduces significant cybersecurity risks. Cyber threat intelligence (CTI) is critical for detecting and mitig...

This article introduces the innovative Quantum Dining Information Brokers Problem, presenting a novel entanglement-based quantum protocol to address it. The scenario involves n information brokers, all located in distinct geographical regions, engagi...

Achieving consensus in group decision-making often involves overcoming significant challenges, particularly reconciling diverse perspectives and mitigating biases hindering agreement. Traditional methods relying on human facilitators are usually cons...

Three-dimensional path planning is critical for the successful operation of unmanned aerial vehicles (UAVs), automated guided vehicles (AGVs), and robots in industrial Internet of Things (IIoT) applications. In 3D path planning, the standard Particle...

To foster the performance of wireless communication while saving energy, the integration of Intelligent Reflecting Surfaces (IRS) into autonomous vehicle (AV) communication networks is considered a powerful technique. This paper proposes a novel IRS-...

Agentic AI systems are a recently emerged and important approach that goes beyond traditional AI, generative AI, and autonomous systems by focusing on autonomy, adaptability, and goal-driven reasoning. This study provides a clear review of agentic AI...

This research introduces a novel de-anonymization technique targeting the Tor network, addressing limitations in prior attack models, particularly concerning router positioning following the introduction of bridge relays. Our method exploits two spec...

The increasing elderly population presents major challenges to traditional healthcare due to the need for continuous care, a shortage of skilled professionals, and increasing medical costs. To address this, smart elderly care homes where multiple res...

In this paper, we introduce an Unmanned Aerial Vehicle (UAV) deployment design with a connectivity constraint for UAV-assisted communication networks. In such networks, multiple UAVs are collaboratively deployed in the air to form a network that real...

The recent worldwide turbulence of events from the pandemic lockdown through increased industrial digitization to geopolitical unease shifted towards new primary targets for the latest generation of DDoS threats. Although certain characteristics of c...

In recent years, the rapid growth of Internet of Things (IoT) technologies has created numerous opportunities across fields such as smart cities, transportation, energy, and healthcare [...]

Optimizing metadata indexing remains critical for enhancing distributed file system performance. The Traditional Log-Structured Merge-Trees (LSM-Trees) architecture, while effective for write-intensive operations, exhibits significant limitations whe...

Recent developments in natural language processing, particularly large language models (LLMs), create new opportunities for literary analysis in underexplored languages like Romanian. This study investigates stylistic heterogeneity and genre blending...

Reinforcement learning (RL) is being used more in medical imaging for segmentation, detection, registration, and classification. This survey provides a comprehensive overview of RL techniques applied in this domain, categorizing the literature based...

Indoor wireless networks face increasing challenges in maintaining stable coverage and performance, particularly with the widespread use of high-frequency Wi-Fi and growing demands from smart home devices. Traditional methods to improve signal qualit...

Malicious actors often exploit persistence mechanisms, such as unauthorized modifications to Windows startup directories or registry keys, to achieve privilege escalation and maintain access on compromised systems. While information technology (IT) t...

As network environments become increasingly dynamic and users’ Quality of Service (QoS) demands grow more diverse, efficient and adaptive routing strategies are urgently needed. However, traditional routing strategies suffer from limitations su...

In dense urban environments and large-scale events, Internet infrastructure often becomes overloaded due to high communication demand. Many of these communications are local and short-lived, exchanged between users in close proximity but still relyin...

The proliferation of fake profiles on social media presents critical cybersecurity and misinformation challenges, necessitating robust and scalable detection mechanisms. Such profiles weaken consumer trust, reduce user engagement, and ultimately harm...

The selection of Data Lifecycle Models (DLMs) in complex data management scenarios necessitates finding a balance between quantitative and qualitative characteristics to ensure regulation, improve performance, and maintain governance requirements. In...

This study aims to conduct a comprehensive comparative evaluation of three transformer-based models, PEGASUS, BART, and T5 variants (SMALL and BASE), for the task of abstractive text summarization. The evaluation spans across three benchmark datasets...

Air pollution threatens human and environmental health worldwide. A Harvard study in partnership with UK institutions found that fossil fuel pollution killed over 8 million people in 2018, accounting for 1 in 5 fatalities worldwide. Iraq, including t...

In software development, software requirement engineering (SRE) is an essential stage that guarantees requirements are clear and unambiguous. However, incomplete inconsistency, and ambiguity in requirement documents often occur, which can cause proje...

Recent advancements in the healthcare sector have reached a pivotal juncture, catalysed by the emergence of Digital Twin (DT) technologies. These innovations facilitate the development of virtual replicas that accurately simulate real-world condition...

Digital Twins (DTs) have become essential tools for improving efficiency, security, and decision-making across various industries. DTs enable deeper insight and more informed decision-making through the creation of virtual replicas of physical entiti...

The graded management of structured sensitive data has become a key challenge in data security governance, particularly amid digital transformation in sectors such as government, finance, and healthcare. The existing methods suffer from limited gener...

The rapid expansion of online learning platforms has necessitated advanced systems to address scalability, personalization, and assessment challenges. This paper presents a comprehensive review of artificial intelligence (AI)-based decision support s...

Current IoT systems are structured around Edge, Fog, and Cloud layers to manage data and resource constraints more effectively. Although several studies have examined IoT simulators from a functional angle, few have combined technical comparisons wit...