Ons Aouedi

Snt University of Luxembourg

The Cloud-Edge-IoT (CEI) continuum integrates edge computing, cloud computing, and the Internet of Things (IoT), fostering rapid Industrial Internet of Things (IIoT) development. Despite its potential, it faces significant challenges, including robustness issues, communication-induced latency, and inconsistent model convergence due to system and da...

The rapid advances in the Internet of Things (IoT) have promoted a revolution in communication technology and offered various customer services. Artificial intelligence (AI) techniques have been exploited to facilitate IoT operations and maximize their potential in modern application scenarios. In particular, the convergence of IoT and AI has led t...

From a telecommunication standpoint, the surge in users and services challenges next-generation networks with escalating traffic demands and limited resources. Accurate traffic prediction can offer network operators valuable insights into network conditions and suggest optimal allocation policies. Recently, spatio-temporal forecasting, employing Gr...

The rapid advances in the Internet of Things (IoT) have promoted a revolution in communication technology and offered various customer services. Artificial intelligence (AI) techniques have been exploited to facilitate IoT operations and maximize their potential in modern application scenarios. In particular, the convergence of IoT and AI has led t...

Human Activity Recognition (HAR) has witnessed remarkable advancements in recent years, driven by the proliferation of wearable devices and the increasing demand for personalized healthcare and activity tracking. Federated Learning (FL) has been used as a promising paradigm for HAR, enabling the collaborative training of machine learning models acr...

As the complexity and scale of modern networks continue to grow, the need for efficient, secure management, and optimization becomes increasingly vital. Digital twin (DT) technology has emerged as a promising approach to address these challenges by providing a virtual representation of the physical network, enabling analysis, diagnosis, emulation,...

Federated Learning (FL) has emerged in edge computing to address privacy concerns in mobile networks. It allows the mobile devices to collaboratively train a model while keeping training data where they were generated. However, in practice, it suffers from several issues such as (i) robustness, due to a single point of failure, (ii) latency, as it...

Recent development in network communication along with the drastic increase in the number of smart devices leads to an explosion in data generation. To this end, intelligent network traffic analysis can help to understand the behavior of connected smart devices and applications as well as provides defense against cyber-attacks. In this line, Machin...

The rapid development of the Internet and smart devices trigger surge in network traffic making its infrastructure more complex and heterogeneous. The predominated usage of mobile phones, wearable devices and autonomous vehicles are examples of distributed networks which generate huge amount of data each and every day. The computational power of th...

Network Traffic Classification enables a number of practical applications ranging from network monitoring to resource management, with security implications as well. Nowadays, traffic classification has become a challenging task in order to distinguish among a variety of applications due to the huge amount of generated traffic. Therefore, developin...

The Internet of Things (IoT) has remarkably evolved over the last few years to realize a wide range of newly emerging services and applications empowered by the unprecedented proliferation of smart devices. The quality of IoT networks heavily relies on the involvement of devices for undertaking functions from data sensing, computation to communicat...

Recent medical applications are largely dominated by the application of Machine Learning (ML) models to assist expert decisions, leading to disruptive innovations in radiology, pathology, genomics, and hence modern healthcare systems in general. Despite the profitable usage of AI-based algorithms, these data-driven methods are facing issues such as...

Security has become a critical issue for Industry4.0 due to different emerging cyber-security threats. Recently, many deep learning (DL) approaches have focused on intrusion detection. However, such approaches often require sending data to a central entity. This in turn raises concerns related to privacy, efficiency, and latency. Despite the huge a...

Network traffic analytics has become a crucial task in order to better understand and manage network resources, especially in the network softwarization era where the implementation of this concept can be done easily with network function virtualization. Currently, many approaches have been proposed to improve the performance of traffic classificat...

The recent development of smart devices has lead to an explosion in data generation and heterogeneity. Hence, current networks should evolve to become more intelligent, efficient, and most importantly, scalable in order to deal with the evolution of network traffic. In recent years, network softwarization has drawn significant attention from both i...

Network traffic classification is a key component for network management, Quality-of-Service management, as well as for network security. Therefore, developing machine learning (ML) methods, which can successfully distinguish network applications from each other, is one of the most important tasks. However, among the classification methods applied...

Recent development in smart devices has lead us to an explosion in data generation and heterogeneity, which requires new network solutions for better analysing and understanding traffic. These solutions should be intelligent and scalable in order to handle the huge amount of data automatically. With the progress of high-performance computing (HPC),...

COVID-19 pandemic has become endemic and has plunged the global community into a perilous situation pervaded with an economic recession, loss of jobs, and the death of thousands of people. It spreads exponentially around the world, affects 213 countries and territories as well as two international conveyances. Yet, the pandemic has neither clinical...

The rapid development of the Internet and smart devices trigger surge in network traffic making its infrastructure more complex and heterogeneous. The predominated usage of mobile phones, wearable devices and autonomous vehicles are examples of distributed networks which generate huge amount of data each and every day. The computational power of th...

The rapid development of smart devices triggers a surge in new traffic and applications. Thus, network traffic classification has become a challenge in modern communications and may be applied to a various range of applications ranging from QoS provisioning to security-related applications. Developing Machine Learning (ML) methods, which can succes...

Network traffic classification is an important task in modern communications. Several approaches have been proposed to improve the performance of differentiating among applications. However, most of them are based on supervised learning where only labeled data are used. In reality, a lot of datasets are partially labeled due to many reasons and unl...

Ambient Intelligence (AmI) is a new paradigm that redefines interaction between humans, sensors and flow of data and information. In AmI, environment is more sensitive and more responsive to the user who acts spontaneously in the foreground, while sensors, machines and intelligent methods act in background. Behind the AmI interfaces, a huge volume...

Due to increase in chronic disease, aging, and medical costs, we are approaching a world where basic healthcare would become out of reach to most people. Fortunately modern technologies like Ambient Intelligence (AmI) and Internet of things (IoT) offer unparalleled benefits, which could improve the quality and efficiency of treatments and according...