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Now showing items 21-28 of 28
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
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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 ...
Active Learning with Noisy Labelers for Improving Classification Accuracy of Connected Vehicles
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Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
Machine learning has emerged as a promising paradigm for enabling connected, automated vehicles to autonomously cruise the streets and react to unexpected situations. Reacting to such situations requires accurate classification ...
To chain or not to chain: A reinforcement learning approach for blockchain-enabled IoT monitoring applications
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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 ...
RF-based drone detection and identification using deep learning approaches: An initiative towards a large open source drone database
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Elsevier B.V.
, 2019 , Article)
The omnipresence of unmanned aerial vehicles, or drones, among civilians can lead to technical, security, and public safety issues that need to be addressed, regulated and prevented. Security agencies are in continuous ...