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Replication Strategy for Spatiotemporal Data Based on Distributed Caching System

The replica strategy in distributed cache can effectively reduce user access delay and improve system performance. However, developing a replica strategy suitable for varied application scenarios is still quite challenging, owing to differences in user access behavior and preferences. In this paper,...

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Detalles Bibliográficos
Autores principales: Xiong, Lian, Yang, Liu, Tao, Yang, Xu, Juan, Zhao, Lun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5795483/
https://www.ncbi.nlm.nih.gov/pubmed/29342897
http://dx.doi.org/10.3390/s18010222
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author Xiong, Lian
Yang, Liu
Tao, Yang
Xu, Juan
Zhao, Lun
author_facet Xiong, Lian
Yang, Liu
Tao, Yang
Xu, Juan
Zhao, Lun
author_sort Xiong, Lian
collection PubMed
description The replica strategy in distributed cache can effectively reduce user access delay and improve system performance. However, developing a replica strategy suitable for varied application scenarios is still quite challenging, owing to differences in user access behavior and preferences. In this paper, a replication strategy for spatiotemporal data (RSSD) based on a distributed caching system is proposed. By taking advantage of the spatiotemporal locality and correlation of user access, RSSD mines high popularity and associated files from historical user access information, and then generates replicas and selects appropriate cache node for placement. Experimental results show that the RSSD algorithm is simple and efficient, and succeeds in significantly reducing user access delay.
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spelling pubmed-57954832018-02-13 Replication Strategy for Spatiotemporal Data Based on Distributed Caching System Xiong, Lian Yang, Liu Tao, Yang Xu, Juan Zhao, Lun Sensors (Basel) Article The replica strategy in distributed cache can effectively reduce user access delay and improve system performance. However, developing a replica strategy suitable for varied application scenarios is still quite challenging, owing to differences in user access behavior and preferences. In this paper, a replication strategy for spatiotemporal data (RSSD) based on a distributed caching system is proposed. By taking advantage of the spatiotemporal locality and correlation of user access, RSSD mines high popularity and associated files from historical user access information, and then generates replicas and selects appropriate cache node for placement. Experimental results show that the RSSD algorithm is simple and efficient, and succeeds in significantly reducing user access delay. MDPI 2018-01-14 /pmc/articles/PMC5795483/ /pubmed/29342897 http://dx.doi.org/10.3390/s18010222 Text en © 2018 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/).
spellingShingle Article
Xiong, Lian
Yang, Liu
Tao, Yang
Xu, Juan
Zhao, Lun
Replication Strategy for Spatiotemporal Data Based on Distributed Caching System
title Replication Strategy for Spatiotemporal Data Based on Distributed Caching System
title_full Replication Strategy for Spatiotemporal Data Based on Distributed Caching System
title_fullStr Replication Strategy for Spatiotemporal Data Based on Distributed Caching System
title_full_unstemmed Replication Strategy for Spatiotemporal Data Based on Distributed Caching System
title_short Replication Strategy for Spatiotemporal Data Based on Distributed Caching System
title_sort replication strategy for spatiotemporal data based on distributed caching system
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5795483/
https://www.ncbi.nlm.nih.gov/pubmed/29342897
http://dx.doi.org/10.3390/s18010222
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