تصفح حسب المؤلف "n 2003097951"
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AirEye: UAV-Based Intelligent DRL Mobile Target Visitation
Soliman, Abdulrahman; Bahri, Mohamad; Izham, Daniel; Mohamed, Amr ( IEEE , 2022 , Conference Paper)From traffic monitoring to livestock tracking, and military reconnaissance to marine discovery, unmanned aerial vehicles (UAVs) are indispensable. Its dependence on a battery for power supply limits the flight time to visit ... -
AirEye: UAV-Based Intelligent DRL Mobile Target Visitation
Soliman, Abdulrahman; Bahri, Mohamad; Izham, Daniel; Mohamed, Amr (2022 , Conference Paper)From traffic monitoring to livestock tracking, and military reconnaissance to marine discovery, unmanned aerial vehicles (UAVs) are indispensable. Its dependence on a battery for power supply limits the flight time to visit ... -
Cross-Layer Optimal Rate Allocation for Heterogeneous Wireless Multicast
Mohamed, Amr; Alnuweiri, Hussein ( Hindawi Publishing Corporation , 2009 , Article)Heterogeneous multicast is an efficient communication scheme especially for multimedia applications running over multihop networks. The term heterogeneous refers to the phenomenon when multicast receivers in the same session ... -
Energy Efficient Cross-Layer Design for Wireless Body Area Monitoring Networks in Healthcare Applications
Awad, Alaa; Mohamed, Amr; El-Sherif, Amr A. ( IEEE , 2013 , Conference Paper)Growing number of patients with chronic diseases requiring constant monitoring has created a major impetus to developing scalable Body Area Sensor Networks (BASNs) for remote health applications. In this paper, to anatomize, ... -
Energy-Harvesting Based Jammer Localization: A Battery-Free Approach in Wireless Sensor Networks
Hussain, Ahmed; Tedeschi, Pietro; Oligeri, Gabriele; Mohamed, Amr; Guizani, Mohsen ( IEEE , 2022 , Conference Paper)Wireless enabling technologies in critical infrastructures are increasing the efficiency of communications. Most of these technologies are vulnerable to jamming attacks. Jamming attacks are among the most effective ... -
Ensemble Classifier for Epileptic Seizure Detection for Imperfect EEG Data
Abualsaud, Khalid; Mahmuddin, Massudi; Saleh, Mohammad; Mohamed, Amr ( Hindawi , 2015 , Article)Brain status information is captured by physiological electroencephalogram (EEG) signals, which are extensively used to study different brain activities.This study investigates the use of a new ensemble classifier to ... -
FEDGAN-IDS: Privacy-preserving IDS using GAN and Federated Learning
Aliya, Tabassum; Erbad, Aiman; Lebda, Wadha; Mohamed, Amr; Guizani, Mohsen ( 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 ... -
Incentive-based Resource Allocation for Mobile Edge Learning
Allahham, Mhd Saria; Mohamed, Amr; Hassanein, Hossam ( IEEE , 2022 , Conference Paper)Mobile Edge Learning (MEL) is a learning paradigm that facilitates training of Machine Learning (ML) models over resource-constrained edge devices. MEL consists of an orchestrator, which represents the model owner of the ... -
Intelligent DRL-Based Adaptive Region of Interest for Delay-Sensitive Telemedicine Applications
Soliman, Abdulrahman; Mohamed, Amr; Yaacoub, Elias; Navkar, Nikhil V.; Erbad, Aiman ( Institute of Electrical and Electronics Engineers Inc. (IEEE) , 2023 , Conference Paper)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 ... -
Jammer Localization in the Internet of Vehicles: Scenarios, Experiments, and Evaluation
Hussain, Ahmed; Abughanam, Nada; Sciancalepore, Savio; Yaacoub, Elias; Mohamed, Amr ( ACM Digital Library , 2022 , Conference Paper)The Internet of Vehicles (IoV) paradigm aims to improve road safety and provide a comfortable driving experience for Internet-connected vehicles, by transmitting early warning and infotainment signals to Internet-connected ... -
MMRL: A Multi-Modal Reinforcement Learning Technique for Energy-efficient Medical IoT Systems
Abo-Eleneen, Amr; Mohamed, Amr ( IEEE , 2021 , Conference Paper)The Internet of Medical Things (IoMT) couples the rapid growth of Internet of things (IoT) technologies with smart health systems, leveraging wireless battery-operated devices for remote health monitoring. Since 2019, a ... -
Multi-Connectivity Management and Orchestration Architecture Integrated With 5g Multi Radio Access Technology Network
Alqahtani, Abdulhadi Jaralla (2020 , Professional Masters Project)The significant growth in the number of devices and the tremendous boost in network/user traffic types and volume as well as the efficiency constraints of 4G innovations have encouraged industry efforts and also financial ... -
On the Modeling of Reliability in Extreme Edge Computing Systems
Allahham, Mhd Saria; Mohamed, Amr; Erbad, Aiman; Hassanein, Hossam ( IEEE , 2022 , Conference Paper)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 ... -
Optimized Resource and Deep Learning Model Allocation in O-RAN Architecture
Makhlouf, Ahmed; Abdellatif, Alaa Awad; Badawy, Ahmed; Mohamed, Amr ( IEEE Computer Society , 2023 , Conference Paper)In the era of 5G and beyond, telecommunication networks tend to move Radio Access Network (RAN) from centralized architecture to a more distributed architecture for greater interoperability and flexibility. Open RAN (O-RAN) ... -
Patient-Driven Network Selection in multi-RAT Health Systems Using Deep Reinforcement Learning
Dawoud, Heba D.M.; Allahham, Mhd Saria; Abdellatif, Alaa Awad; Mohamed, Amr; Erbad, Aiman; Guizani, Mohsen... more authors ... less authors ( Institute of Electrical and Electronics Engineers Inc. , 2021 , Conference Paper)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. ... -
PLS Performance Analysis of a Hybrid NOMA-OMA based IoT System with Mobile Sensors
Chamkhia, Hela; Erbad, Aiman; Al-Ali, Abdullah; Mohamed, Amr; Refaey, Ahmed; Guizani, Mohsen... more authors ... less authors ( Institute of Electrical and Electronics Engineers Inc. , 2022 , Conference Paper)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 ... -
Region of Interest Optimization for Delay-sensitive Telemedicine Applications
Elmoghazy, Somayya; Yaacoub, Elias; Navkar, Nikhil V.; Mohamed, Amr; Erbad, Aiman ( IEEE , 2022 , Conference Paper)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
Saadat, Hassan; Allahham, Mhd Saria; Abdellatif, Alaa Awad; Erbad, Aiman; Mohamed, Amr (2022 , Conference Paper)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 ... -
RL-Based Federated Learning Framework Over Blockchain (RL-FL-BC)
Riahi, Ali; Mohamed, Amr; Erbad, Aiman ( IEEE , 2023 , Article)Federated learning (FL) paradigms aim to amalgamate diverse data properties stored locally at each user, while preserving data privacy through sharing users’ learning experiences and iteratively aggregating their ... -
RLENS: RL-based Energy-Efficient Network Selection Framework for IoMT
Abo-Eleneen, Amr; Abdellatif, Alaa Awad; Mohamed, Amr; Erbad, Aiman ( IEEE , 2022 , Conference Paper)With the emergence of smart health (s-health) applications and services, several requirements for quality have arisen to foresee and react instantaneously to emergency circumstances. Such requirements demand fast-acting ...