Browsing by Author "Erbad, Aiman"
Now showing items 21-40 of 70
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Dynamic Network Slicing and Resource Allocation for 5G-and-Beyond Networks
Abdellatif, Alaa Awad; Mohamed, Amr; Erbad, Aiman; Guizani, Mohsen ( Institute of Electrical and Electronics Engineers Inc. , 2022 , Conference Paper)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 ... -
Edge computing for interactive media and video streaming
Bilal,Kashif; Erbad, Aiman ( Institute of Electrical and Electronics Engineers Inc. , 2017 , Conference Paper)Video streaming and computer games are among the most popular and highest bandwidth consuming media in the Internet. Video contents consume around 70% of the total bandwidth usage in the Internet today. Advancements in ... -
Efficient EEG mobile edge computing and optimal resource allocation for smart health applications
Al-Marridi, Abeer Z.; Mohamed, Amr; Erbad, Aiman; Al-Ali, Abdulla; Guizani, Mohsen ( Institute of Electrical and Electronics Engineers Inc. , 2019 , Conference Paper)In the past few years, a rapid increase in the number of patients requiring constant monitoring, which inspires researchers to develop intelligent and sustainable remote smart healthcare services. However, the transmission ... -
Empirical performance evaluation of QUIC protocol for Tor anonymity network
Basyoni, Lamiaa; Erbad, Aiman; Alsabah, Mashael; Fetais, Noora; Guizani, Mohsen ( Institute of Electrical and Electronics Engineers Inc. , 2019 , Conference Paper)Tor's anonymity network is one of the most widely used anonymity networks online, it consists of thousands of routers run by volunteers. Tor preserves the anonymity of its users by relaying the traffic through a number of ... -
Energy-Efficient Device Assignment and Task Allocation in Multi-Orchestrator Mobile Edge Learning
Allahham, Mhd Saria; Sorour, Sameh; Mohamed, Amr; Erbad, Aiman; Guizani, Mohsen ( Institute of Electrical and Electronics Engineers Inc. , 2021 , Conference Paper)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 ... -
ENHANCING THE PERFORMANCE AND SECURITY OF ANONYMOUS COMMUNICATION NETWORKS
BASYONI, LAMIAA MOHAMED (2022 , Dissertation)With the increasing importance of the Internet in our daily lives, the private information of millions of users is prone to more security risks. Users data are collected either for commercial purposes and sold by service ... -
Fault and performance management in multi-cloud based NFV using shallow and deep predictive structures
Gupta, Lav; Samaka, M.; Jain, Raj; Erbad, Aiman; Bhamare, Deval; Chan, H. Anthony... more authors ... less authors ( Institute of Electrical and Electronics Engineers Inc. , 2017 , Conference Paper)Deployment of Network Function Virtualization (NFV) over multiple clouds accentuates its advantages like flexibility of virtualization, proximity to customers and lower total cost of operation. However, NFV over multiple ... -
Fault and performance management in multi-cloud based NFV using shallow and deep predictive structures
Gupta, Lav; Samaka, M.; Jain, Raj; Erbad, Aiman; Bhamare, Deval; Chan, H Anthony... more authors ... less authors ( Springer , 2017 , Article)Deployment of network function virtualization (NFV) over multiple clouds accentuates its advantages such as flexibility of virtualization, proximity to customers and lower total cost of operation. However, NFV over multiple ... -
Feasibility of Supervised Machine Learning for Cloud Security
Bhamare, Deval; Salman, Tara; Samaka, Mohammed; Erbad, Aiman; Jain, Raj ( Institute of Electrical and Electronics Engineers Inc. , 2017 , Conference Paper)Cloud computing is gaining significant attention, however, security is the biggest hurdle in its wide acceptance. Users of cloud services are under constant fear of data loss, security threats and availability issues. ... -
Federated Learning for UAV Swarms under Class Imbalance and Power Consumption Constraints
Mrad, Ilyes; Samara, Lutfi; Abdellatif, Alaa Awad; Al-Abbasi, Abubakr; Hamila, Ridha; Erbad, Aiman... more authors ... less authors ( IEEE , 2021 , Conference Paper)The usage of unmanned aerial vehicles (UAVs) in civil and military applications continues to increase due to the numerous advantages that they provide over conventional approaches. Despite the abundance of such advantages, ... -
Federated Learning in NOMA Networks: Convergence, Energy and Fairness-Based Design
Mrad, Ilyes; Samara, Lutfi; Al-Abbasi, Abubakr; Hamila, Ridha; Erbad, Aiman; Kiranyaz, Serkan... more authors ... less authors ( IEEE , 2022 , Conference Paper)Federated Learning (FL) is a collaborative machine learning (ML) approach, where different nodes in a network contribute to learning the model parameters. In addition, FL provides several attractive features such as data ... -
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 ... -
Green data center networks: A holistic survey and design guidelines
Baccour, Emna; Foufou, Sebti; Hamila, Ridha; Erbad, Aiman ( Institute of Electrical and Electronics Engineers Inc. , 2019 , Conference Paper)Data Center Networks (DCNs) are attracting immense interest from the industry, research and academia to keep pace with the increase of Internet services demands. One of the major concerns that draws the attention of ... -
Hierarchical Federated Learning over HetNets enabled by Wireless Energy Transfer
Hamdi, Rami; Said, Ahmed Ben; Erbad, Aiman; Mohamed, Amr; Hamdi, Mounir; Guizani, Mohsen... more authors ... less authors ( Institute of Electrical and Electronics Engineers Inc. , 2021 , Conference Paper)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
Chkirbene, Zina; Eltanbouly, Sohaila; Bashendy, May; Alnaimi, Noora; Erbad, Aiman ( IEEE , 2020 , Conference Paper)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 ... -
Impact of multiple video representations in live streaming: A cost, bandwidth, and QoE analysis
Bila, Kashif; Erbad, Aiman ( Institute of Electrical and Electronics Engineers Inc. , 2017 , Conference Paper)Video streaming is one of the most popular and highest bandwidth consumers within the Internet today. Cloud's elastic and pay-per-use model offers viable solution to varying demands of heterogeneous viewers for large-scale ... -
Important complexity reduction of random forest in multi-classification problem
Hassine, Kawther; Erbad, Aiman; Hamila, Ridha ( Institute of Electrical and Electronics Engineers Inc. , 2019 , Conference Paper)Algorithm complexity in machine learning problems has been a real concern especially with large-scaled systems. By increasing data dimensionality, a particular emphasis is placed on designing computationally efficient ... -
Joint learning and optimization for Federated Learning in NOMA-based networks
Mrad, Ilyes; Hamila, Ridha; Erbad, Aiman; Gabbouj, Moncef ( Elsevier , 2023 , Article)Over the past decade, the usage of machine learning (ML) techniques have increased substantially in different applications. Federated Learning (FL) refers to collaborative techniques that avoid the exchange of raw data ... -
Machine Learning for Anomaly Detection and Categorization in Multi-Cloud Environments
Salman, Tara; Bhamare, Deval; Erbad, Aiman; Jain, Raj; Samaka, Mohammed ( Institute of Electrical and Electronics Engineers Inc. , 2017 , Conference Paper)Cloud computing has been widely adopted by application service providers (ASPs) and enterprises to reduce both capital expenditures (CAPEX) and operational expenditures (OPEX). Applications and services previously running ... -
Machine Learning Screening of COVID-19 Patients Based on X-ray Images for Imbalanced Classes
Mrad, Ilyes; Hamila, Ridha; Erbad, Aiman; Hamid, Tahir; Mazhar, Rashid; Al-Emadi, Nasser... more authors ... less authors ( IEEE , 2021 , Conference Paper)COVID-19 is a virus that has infected more than one hundred and fifty million people and caused more than three million deaths by 13th of Mai 2021 and is having a catastrophic effect on the world population's safety. ...