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السجلات المعروضة 21 -- 30 من 43
QoE-Aware Resource Allocation for Crowdsourced Live Streaming: A Machine Learning Approach
(
Institute of Electrical and Electronics Engineers Inc.
, 2019 , Conference Paper)
Driven by the tremendous technological advancement of personal devices and the prevalence of wireless mobile network accesses, the world has witnessed an explosion in crowdsourced live streaming. Ensuring a better viewers ...
An Intelligent Resource Reservation for Crowdsourced Live Video Streaming Applications in Geo-Distributed Cloud Environment
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
Crowdsourced live video streaming (livecast) services such as Facebook Live, YouNow, Douyu, and Twitch are gaining more momentum recently. Allocating the limited resources in a cost-effective manner while maximizing the ...
Hierarchical Federated Learning for Collaborative IDS in IoT Applications
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Conference Paper)
As the Internet-of-Things devices are being very widely adopted in all fields, such as smart houses, healthcare, and transportation, extremely huge amounts of data are being gathered, shared, and processed. This fact raises ...
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 ...
Deep Reinforcement Learning for Network Selection over Heterogeneous Health Systems
(
IEEE Computer Society
, 2022 , Article)
Smart health systems improve our quality oflife by integrating diverse information and technologies into health and medical practices. Such technologies can significantly improve the existing health services. However, ...
Optimal User-Edge Assignment in Hierarchical Federated Learning Based on Statistical Properties and Network Topology Constraints
(
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
(
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 ...
Communication-efficient hierarchical federated learning for IoT heterogeneous systems with imbalanced data
(
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 ...