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Title: | End-to-End QoS "Smart Queue" Management Algorithms and Traffic Prioritization Mechanisms for Narrow-Band Internet of Things Services in 4G/5G Networks | Authors: | Beshley, Mykola Kryvinska, Natalia Seliuchenko, Marian Beshley, Halyna Shakshuki, Elhadi M. YASAR, Ansar |
Issue Date: | 2020 | Publisher: | MDPI | Source: | Sensors (Basel), 20 (8) (Art N° 2324) | Abstract: | This paper proposes a modified architecture of the Long-Term Evolution (LTE) mobile network to provide services for the Internet of Things (IoT). This is achieved by allocating a narrow bandwidth and transferring the scheduling functions from the eNodeB base station to an NB-IoT controller. A method for allocating uplink and downlink resources of the LTE/NB-IoT hybrid technology is applied to ensure the Quality of Service (QoS) from end-to-end. This method considers scheduling traffic/resources on the NB-IoT controller, which allows eNodeB planning to remain unchanged. This paper also proposes a prioritization approach within the IoT traffic to provide End-to-End (E2E) QoS in the integrated LTE/NB-IoT network. Further, we develop "smart queue" management algorithms for the IoT traffic prioritization. To demonstrate the feasibility of our approach, we performed a number of experiments using simulations. We concluded that our proposed approach ensures high end-to-end QoS of the real-time traffic by reducing the average end-to-end transmission delay. | Keywords: | Internet of Things (IoT);Long-Term Evolution (LTE) standard for wireless broadband;Narrow-Band IoT (NB-IoT);prioritization;Quality of Services (QoS);traffic scheduling;4G/5G broadband cellular network technology | Document URI: | http://hdl.handle.net/1942/34564 | e-ISSN: | 1424-8220 | DOI: | 10.3390/s20082324 | ISI #: | WOS:000533346400166 | Rights: | 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2021 |
Appears in Collections: | Research publications |
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sensors-20-02324-v2.pdf | Published version | 11.7 MB | Adobe PDF | View/Open |
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