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ONSRA: An Optimal Network Selection and Resource Allocation Framework in multi-RAT Systems
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Conference Paper)
The rapid production of mobile and wearable devices along with the wireless applications boom is continuing to evolve everyday. This motivates network operators to integrate and exploit wireless spectrum across multiple ...
Machine Learning Based Cloud Computing Anomalies Detection
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Article)
Recently, machine learning algorithms have been proposed to design new security systems for anomalies detection as they exhibit fast processing with real-time predictions. However, one of the major challenges in machine ...
Service-Less Video Multicast in 5G: Enablers and Challenges
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Article)
The massive upsurge in production and demand of crowdsourced live streaming necessitates feasible and cost effective solutions in future cellular networks. Video multicast is one of the viable options to deliver live video ...
Energy-Aware Distributed Edge ML for mHealth Applications with Strict Latency Requirements
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
Edge machine learning (Edge ML) is expected to serve as a key enabler for real-time mobile health (mHealth) applications. However, its reliability is governed by the limited energy and computing resources of user equipment ...
A Weighted Machine Learning-Based Attacks Classification to Alleviating Class Imbalance
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
The Industrial Internet of Things (IIoT) has become very popular in recent years. However, IIoT is still an attractive and vulnerable target for attackers to exploit and experiment with different types of attacks. To ...
Multicast at Edge: An Edge Network Architecture for Service-Less Crowdsourced Live Video Multicast
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
Using smartphones, tablets, and other portable/handheld devices, we have become more reliant on the video streaming services for entertainment and remote work. Mobile data traffic has grown eighteen folds over the past ...
I-SEE: Intelligent, Secure, and Energy-Efficient Techniques for Medical Data Transmission Using Deep Reinforcement Learning
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
The rapid evolution of remote health monitoring applications is foreseen to be a crucial solution for facing an unpredictable health crisis and improving the quality of life. However, such applications come with many ...
Reinforcement learning approaches for efficient and secure blockchain-powered smart health systems
(
Elsevier B.V.
, 2021 , Article)
Emerging technological innovation toward e-Health transition is a worldwide priority for ensuring people's quality of life. Hence, secure exchange and analysis of medical data amongst diverse organizations would increase ...
A Survey of Machine and Deep Learning Methods for Internet of Things (IoT) Security
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Article)
The Internet of Things (IoT) integrates billions of smart devices that can communicate with one another with minimal human intervention. IoT is one of the fastest developing fields in the history of computing, with an ...
Collaborative hierarchical caching and transcoding in edge network with CE-D2D communication
(
Academic Press
, 2020 , Article)
To support multimedia applications, Mobile Edge Computing (MEC) servers offer storage and computing capacities to handle videos close to end-users. However, the high load in peak hours consumes the limited available bandwidth ...