IoT Traffic Shaping and the Massive Access Problem
Author:
Affiliation:
1. Inst. of Theoretical & Applied Informatics,Polish Ac. Sci.,Gliwice,PL,44-100
2. Columbia University,Dept. Industrial Eng. & Operations Res. & Center for Applied Probability,New York,NY,USA,10027
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9837954/9838246/09839054.pdf?arnumber=9839054
Reference48 articles.
1. On Leveraging Machine and Deep Learning for Throughput Prediction in Cellular Networks: Design, Performance, and Challenges
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1. Identifying Network Congestion Using Knowledge Graphs and Link Prediction;Proceedings of the IEEE/ACM 16th International Conference on Utility and Cloud Computing;2023-12-04
2. Traffic Management in IoT Backbone Networks Using GNN and MAB with SDN Orchestration;Sensors;2023-08-10
3. A Survey of Traffic Shaping Technology in Internet of Things;IEEE Access;2023
4. MOSAL: A Subspace-Based Forecasting Algorithm for Throughput Maximization in IoT Networks;IEEE Sensors Journal;2022-12-15
5. Improving Massive Access to IoT Gateways;Performance Evaluation;2022-10
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