Browsing by Author "Erbad, Aiman"
Now showing items 1-20 of 30
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3-D Stochastic Geometry-Based Modeling and Performance Analysis of Efficient Security Enhancement Scheme for IoT Systems
( Institute of Electrical and Electronics Engineers Inc. , 2022 , Article)Internet of Things (IoT) systems are becoming core building blocks for different services and applications supporting every day's life. The heterogeneous nature of IoT devices and the complex use scenarios make it hard to ... -
Deep Reinforcement Learning for Network Selection over Heterogeneous Health Systems
( IEEE Computer Society , 2022 , Article)Smart health systems improve our quality oflife by integrating diverse information and technologies into health and medical practices. Such technologies can significantly improve the existing health services. However, ... -
Dynamic Network Slicing and Resource Allocation for 5G-and-Beyond Networks
( Institute of Electrical and Electronics Engineers Inc. , 2022 , Conference)5G networks are designed not only to transport data, but also to process them while supporting a vast number of services with different key Performance Indicators (KPIs). Network virtualization has emerged to enable this ... -
Energy-Efficient Device Assignment and Task Allocation in Multi-Orchestrator Mobile Edge Learning
( Institute of Electrical and Electronics Engineers Inc. , 2021 , Conference)Mobile Edge Learning (MEL) is a decentralized learning paradigm that enables resource-constrained IoT devices to either learn a shared model without sharing the data, or to distribute the learning task with the data to ... -
FEDGAN-IDS: Privacy-preserving IDS using GAN and Federated Learning
( Elsevier , 2022 , Article)Federated Learning (FL) is a promising distributed training model that aims to minimize the data sharing to enhance privacy and performance. FL requires sufficient and diverse training data to build efficient models. Lack ... -
Hierarchical Federated Learning over HetNets enabled by Wireless Energy Transfer
( Institute of Electrical and Electronics Engineers Inc. , 2021 , Conference)Training centralized machine learning (ML) models becomes infeasible in wireless networks due to the increasing number of internet of things (IoT) and mobile devices and the prevalence of the learning algorithms to adapt ... -
Hybrid Machine Learning for Network Anomaly Intrusion Detection
( IEEE , 2020 , Conference)In this paper, a hybrid approach of combing two machine learning algorithms is proposed to detect the different possible attacks by performing effective feature selection and classification. This system uses Random Forest ... -
Intelligent DRL-Based Adaptive Region of Interest for Delay-Sensitive Telemedicine Applications
( Institute of Electrical and Electronics Engineers Inc. (IEEE) , 2023 , Conference)Telemedicine applications have recently received substantial potential and interest, especially after the COVID-19 pandemic. Remote experience will help people get their complex surgery done or transfer knowledge to local ... -
Machine Learning Techniques for Network Anomaly Detection: A Survey
( IEEE , 2020 , Conference)Nowadays, distributed data processing in cloud computing has gained increasing attention from many researchers. The intense transfer of data has made the network an attractive and vulnerable target for attackers to exploit ... -
Multi-Agent Reinforcement Learning for Network Selection and Resource Allocation in Heterogeneous Multi-RAT Networks
( Institute of Electrical and Electronics Engineers Inc. , 2022 , Article)The rapid production of mobile devices along with the wireless applications boom is continuing to evolve daily. This motivates the exploitation of wireless spectrum using multiple Radio Access Technologies (multi-RAT) and ... -
On Designing Smart Agents for Service Provisioning in Blockchain-Powered Systems
( IEEE Computer Society , 2022 , Article)Service provisioning systems assign users to service providers according to allocation criteria that strike an optimal trade-off between users' Quality of Experience (QoE) and the operation cost endured by providers. These ... -
On the Modeling of Reliability in Extreme Edge Computing Systems
( IEEE , 2022 , Conference)Extreme edge computing (EEC) refers to the end-most part of edge computing wherein computational tasks and edge services are deployed only on extreme edge devices (EEDs). EEDs are consumer or user-owned devices that offer ... -
Patient-Driven Network Selection in multi-RAT Health Systems Using Deep Reinforcement Learning
( Institute of Electrical and Electronics Engineers Inc. , 2021 , Conference)The recent pandemic along with the rapid increase in the number of patients that require continuous remote monitoring imposes several challenges to support the high quality of services (QoS) in remote health applications. ... -
Pervasive AI for IoT applications: A Survey on Resource-efficient Distributed Artificial Intelligence
( Institute of Electrical and Electronics Engineers Inc. , 2022 , Article)Artificial intelligence (AI) has witnessed a substantial breakthrough in a variety of Internet of Things (IoT) applications and services, spanning from recommendation systems and speech processing applications to robotics ... -
PLS Performance Analysis of a Hybrid NOMA-OMA based IoT System with Mobile Sensors
( Institute of Electrical and Electronics Engineers Inc. , 2022 , Conference)With the advent of Internet of Things (IoT) systems, privacy and integrity of messages are becoming critical issues and are threatened, especially with mobile sensors. The broadcast nature of wireless communications increase ... -
Preliminary design and evaluation of a remote tele-mentoring system for minimally invasive surgery
( Springer Nature , 2022 , Article)Background: Tele-mentoring during surgery facilitates the transfer of surgical knowledge from a mentor (specialist surgeon) to a mentee (operating surgeon). The aim of this work is to develop a tele-mentoring system tailored ... -
QDRL: QoS-Aware Deep Reinforcement Learning Approach for Tor's Circuit Scheduling
( IEEE Computer Society , 2022 , Article)Tor is a popular anonymity network adopted by more than two million users to preserve their privacy. Tor was mainly developed as a low-latency network to support interactive web browsing and messaging applications. However, ... -
QoE-Aware Resource Allocation For Crowdsourced Live Streaming: A Machine Learning Approach
(2019 , Master Thesis)In the last decade, empowered by the technological advancements of mobile devices and the revolution of wireless mobile network access, the world has witnessed an explosion in crowdsourced live streaming. Ensuring a ... -
Region of Interest Optimization for Delay-sensitive Telemedicine Applications
( IEEE , 2022 , Conference)Telemedicine is a rising technology that is gaining a lot of interest in the recent decades. Several applications of telemedicine are delay-sensitive and need to be operated in real-time. One of which is surgical tele-mentoring ... -
RL-Assisted Energy-Aware User-Edge Association for IoT-based Hierarchical Federated Learning
(2022 , Conference)The extremely heavy global reliance on IoT devices is causing enormous amounts of data to be gathered and shared in IoT networks. Such data need to efficiently be used in training and deploying of powerful artificially ...
