Toward QoS Prediction Based on Temporal Transformers for IoT Applications-Reference-Cited by-同舟云学术

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Toward QoS Prediction Based on Temporal Transformers for IoT Applications

Published:2022-12 Issue:4 Volume:19 Page:4010-4027
ISSN:1932-4537
Container-title:IEEE Transactions on Network and Service Management
language:
Short-container-title:IEEE Trans. Netw. Serv. Manage.

Author:

Hameed Aroosa¹,Violos John¹^ORCID,Leivadeas Aris¹^ORCID,Santi Nina²,Grunblatt Remy³^ORCID,Mitton Nathalie²^ORCID

Affiliation:

1. Department of Software and Information Technology Engineering, École de technologie supérieure, University of Quebec, Montreal, QC, Canada

2. FUN Research Group, INRIA Lille-Nord, Villeneuve-d’Ascq, France

3. SAMOVAR, Télécom SudParis, Institut Polytechnique de Paris, évry, France

Funder

CHIST-ERA-18-SDCDN-003 DRUID-NET project “Edge Computing Resource Allocation for Dynamic Networks.”

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Networks and Communications

Link

http://xplorestaging.ieee.org/ielx7/4275028/10034788/09930825.pdf?arnumber=9930825

Reference27 articles.

1. A Machine Learning Regression Approach for Throughput Estimation in an IoT Environment

2. Multi-Parametric Analysis of Reliability and Energy Consumption in IoT: A Deep Learning Approach

3. EdgeLSTM: Towards Deep and Sequential Edge Computing for IoT Applications

5. A Study of Throughput Prediction using Convolutional Neural Network over Factory Environment

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1. TPMCF: Temporal QoS Prediction Using Multi-Source Collaborative Features;IEEE Transactions on Network and Service Management;2024-08

2. AoI-Aware, Digital Twin-Empowered IoT Query Services in Mobile Edge Computing;IEEE/ACM Transactions on Networking;2024-08

3. An interpretable hybrid deep learning model for flood forecasting based on Transformer and LSTM;Journal of Hydrology: Regional Studies;2024-08

4. IoT Pro-Active SDN: A Smart Predictive-Based Approach for IoT Devices in SDN;2024 11th International Conference on Wireless Networks and Mobile Communications (WINCOM);2024-07-23

5. CSformer: Enhancing deep learning efficiency for intelligent IoT;Computer Communications;2024-01

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