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A Semantic and Knowledge-Based Approach for Handover Management

Handover Management (HM) is pivotal for providing service continuity, enormous reliability and extreme-low latency, and meeting sky-high data rates, in wireless communications. Current HM approaches based on a single criterion may lead to unnecessary and frequent handovers due to a partial network v...

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Autores principales: Vivas, Fulvio Yesid, Caicedo, Oscar Mauricio, Nieves, Juan Carlos
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8235340/
https://www.ncbi.nlm.nih.gov/pubmed/34205492
http://dx.doi.org/10.3390/s21124234
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author Vivas, Fulvio Yesid
Caicedo, Oscar Mauricio
Nieves, Juan Carlos
author_facet Vivas, Fulvio Yesid
Caicedo, Oscar Mauricio
Nieves, Juan Carlos
author_sort Vivas, Fulvio Yesid
collection PubMed
description Handover Management (HM) is pivotal for providing service continuity, enormous reliability and extreme-low latency, and meeting sky-high data rates, in wireless communications. Current HM approaches based on a single criterion may lead to unnecessary and frequent handovers due to a partial network view that is constrained to information about link quality. In turn, HM approaches based on multicriteria may present a failure of handovers and wrong network selection, decreasing the throughput and increasing the packet loss in the network. This paper proposes SIM-Know, an approach for improving HM. SIM-Know improves HM by including a Semantic Information Model (SIM) that enables context-aware and multicriteria handover decisions. SIM-Know also introduces a SIM-based distributed Knowledge Base Profile (KBP) that provides local and global intelligence to make contextual and proactive handover decisions. We evaluated SIM-Know in an emulated wireless network. When the end-user device moves at low and moderate speeds, the results show that our approach outperforms the Signal Strong First (SSF, single criterion approach) and behaves similarly to the Analytic Hierarchy Process combined with the Technique for Order Preferences by Similarity to the Ideal Solution (AHP-TOPSIS, multicriteria approach) regarding the number of handovers and the number of throughput drops. SSF outperforms SIM-Know and AHP-TOPSIS regarding the handover latency metric because SSF runs a straightforward process for making handover decisions. At high speeds, SIM-Know outperforms SSF and AHP-TOPSIS regarding the number of handovers and the number of throughput drops and, further, improves the throughput, delay, jitter, and packet loss in the network. Considering the obtained results, we conclude that SIM-Know is a practical and attractive solution for cognitive HM.
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spelling pubmed-82353402021-06-27 A Semantic and Knowledge-Based Approach for Handover Management Vivas, Fulvio Yesid Caicedo, Oscar Mauricio Nieves, Juan Carlos Sensors (Basel) Article Handover Management (HM) is pivotal for providing service continuity, enormous reliability and extreme-low latency, and meeting sky-high data rates, in wireless communications. Current HM approaches based on a single criterion may lead to unnecessary and frequent handovers due to a partial network view that is constrained to information about link quality. In turn, HM approaches based on multicriteria may present a failure of handovers and wrong network selection, decreasing the throughput and increasing the packet loss in the network. This paper proposes SIM-Know, an approach for improving HM. SIM-Know improves HM by including a Semantic Information Model (SIM) that enables context-aware and multicriteria handover decisions. SIM-Know also introduces a SIM-based distributed Knowledge Base Profile (KBP) that provides local and global intelligence to make contextual and proactive handover decisions. We evaluated SIM-Know in an emulated wireless network. When the end-user device moves at low and moderate speeds, the results show that our approach outperforms the Signal Strong First (SSF, single criterion approach) and behaves similarly to the Analytic Hierarchy Process combined with the Technique for Order Preferences by Similarity to the Ideal Solution (AHP-TOPSIS, multicriteria approach) regarding the number of handovers and the number of throughput drops. SSF outperforms SIM-Know and AHP-TOPSIS regarding the handover latency metric because SSF runs a straightforward process for making handover decisions. At high speeds, SIM-Know outperforms SSF and AHP-TOPSIS regarding the number of handovers and the number of throughput drops and, further, improves the throughput, delay, jitter, and packet loss in the network. Considering the obtained results, we conclude that SIM-Know is a practical and attractive solution for cognitive HM. MDPI 2021-06-21 /pmc/articles/PMC8235340/ /pubmed/34205492 http://dx.doi.org/10.3390/s21124234 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Vivas, Fulvio Yesid
Caicedo, Oscar Mauricio
Nieves, Juan Carlos
A Semantic and Knowledge-Based Approach for Handover Management
title A Semantic and Knowledge-Based Approach for Handover Management
title_full A Semantic and Knowledge-Based Approach for Handover Management
title_fullStr A Semantic and Knowledge-Based Approach for Handover Management
title_full_unstemmed A Semantic and Knowledge-Based Approach for Handover Management
title_short A Semantic and Knowledge-Based Approach for Handover Management
title_sort semantic and knowledge-based approach for handover management
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8235340/
https://www.ncbi.nlm.nih.gov/pubmed/34205492
http://dx.doi.org/10.3390/s21124234
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