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Optimal User-Edge Assignment in Hierarchical Federated Learning Based on Statistical Properties and Network Topology Constraints
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IEEE Computer Society
, 2022 , Article)
Distributed learning algorithms aim to leverage distributed and diverse data stored at users' devices to learn a global phenomena by performing training amongst participating devices and periodically aggregating their local ...
A Weighted Machine Learning-Based Attacks Classification to Alleviating Class Imbalance
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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
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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
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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 ...
Communication-efficient hierarchical federated learning for IoT heterogeneous systems with imbalanced data
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Elsevier B.V.
, 2022 , Article)
Federated Learning (FL) is a distributed learning methodology that allows multiple nodes to cooperatively train a deep learning model, without the need to share their local data. It is a promising solution for telemonitoring ...
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 ...
QuicTor: Enhancing Tor for Real-Time Communication Using QUIC Transport Protocol
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Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
In the past decades, the internet has emerged as the fastest way to access information. However, this revolutionary information age comes with its own set of challenges. The privacy of Internet users is at increasing risk ...
B5G: Predictive Container Auto-Scaling for Cellular Evolved Packet Core
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Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
In order to maintain a satisfactory performance in the midst of rapid growth of mobile traffic, the mobile network infrastructure needs to be scaled. Thus there has been significant interest in scalability of mobile core ...
To chain or not to chain: A reinforcement learning approach for blockchain-enabled IoT monitoring applications
(
Elsevier B.V.
, 2020 , Article)
Traceability and autonomous business logic execution are highly desirable features in IoT monitoring applications. Traceability enables verifying signals history for security or analytical purposes. On the other hand, the ...
TIDCS: A Dynamic Intrusion Detection and Classification System Based Feature Selection
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Institute of Electrical and Electronics Engineers Inc.
, 2020 , Article)
Machine learning techniques are becoming mainstream in intrusion detection systems as they allow real-time response and have the ability to learn and adapt. By using a comprehensive dataset with multiple attack types, a ...