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Distributed CNN Inference on Resource-Constrained UAVs for Surveillance Systems: Design and Optimization
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Institute of Electrical and Electronics Engineers Inc.
, 2022 , Article)
Unmanned aerial vehicles (UAVs) have attracted great interest in the last few years owing to their ability to cover large areas and access difficult and hazardous target zones, which is not the case of traditional systems ...
RL-PDNN: Reinforcement Learning for Privacy-Aware Distributed Neural Networks in IoT Systems
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Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
Due to their high computational and memory demand, deep learning applications are mainly restricted to high-performance units, e.g., cloud and edge servers. Particularly, in Internet of Things (IoT) systems, the data ...
An Intelligent Resource Reservation for Crowdsourced Live Video Streaming Applications in Geo-Distributed Cloud Environment
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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 ...
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 ...
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 ...
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 ...