End-to-End QoS "Smart Queue" Management Algorithms and Traffic Prioritization Mechanisms for Narrow-Band Internet of...

Area of Science:

• Telecommunications Engineering
• Network Architecture
• Internet of Things (IoT)

Background:

• Existing Long-Term Evolution (LTE) networks face challenges in efficiently supporting diverse Internet of Things (IoT) services.
• Optimizing Quality of Service (QoS) for delay-sensitive IoT applications within integrated network infrastructures is crucial.

Purpose of the Study:

• To propose a modified LTE architecture for seamless IoT service integration.
• To enhance end-to-end QoS for IoT traffic within a hybrid LTE/NB-IoT network.
• To develop advanced traffic management algorithms for prioritized IoT data delivery.

Main Methods:

• Modified LTE architecture with an NB-IoT controller for scheduling functions.
• Narrow bandwidth allocation for IoT services.
• Hybrid LTE/NB-IoT resource allocation for uplink and downlink.
• Development of "smart queue" management algorithms for traffic prioritization.

Main Results:

• Demonstrated feasibility through simulations.
• Ensured high end-to-end QoS for real-time IoT traffic.
• Significantly reduced average end-to-end transmission delay.

Conclusions:

• The proposed modified LTE architecture effectively supports IoT services.
• The integrated LTE/NB-IoT approach with smart queue management guarantees E2E QoS.
• The solution offers a viable method for improving IoT communication efficiency and reliability.