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Multi-Location-Aware Joint Optimization of Content Caching and Delivery for Backhaul-Constrained UDN

Mobile edge caching is regarded as a promising way to reduce the backhaul load of the base stations (BSs). However, the capacity of BSs’ cache tends to be small, while mobile users’ content preferences are diverse. Furthermore, both the locations of users and user-BS association are uncertain in wir...

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Autores principales: Jing, Wenpeng, Wen, Xiangming, Lu, Zhaoming, Zhang, Haijun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6603776/
https://www.ncbi.nlm.nih.gov/pubmed/31146353
http://dx.doi.org/10.3390/s19112449
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author Jing, Wenpeng
Wen, Xiangming
Lu, Zhaoming
Zhang, Haijun
author_facet Jing, Wenpeng
Wen, Xiangming
Lu, Zhaoming
Zhang, Haijun
author_sort Jing, Wenpeng
collection PubMed
description Mobile edge caching is regarded as a promising way to reduce the backhaul load of the base stations (BSs). However, the capacity of BSs’ cache tends to be small, while mobile users’ content preferences are diverse. Furthermore, both the locations of users and user-BS association are uncertain in wireless networks. All of these pose great challenges on the content caching and content delivery. This paper studies the joint optimization of the content placement and content delivery schemes in the cache-enabled ultra-dense small-cell network (UDN) with constrained-backhaul link. Considering the differences in decision time-scales, the content placement and content delivery are investigated separately, but their interplay is taken into consideration. Firstly, a content placement problem is formulated, where the uncertainty of user-BS association is considered. Specifically, different from the existing works, the specific multi-location request pattern is considered that users tend to send content requests from more than one but limited locations during one day. Secondly, a user-BS association and wireless resources allocation problem is formulated, with the objective of maximizing users’ data rates under the backhaul bandwidth constraint. Due to the non-convex nature of these two problems, the problem transformation and variables relaxation are adopted, which convert the original problems into more tractable forms. Then, based on the convex optimization methods, a content placement algorithm, and a cache-aware user association and resources allocation algorithm are proposed, respectively. Finally, simulation results are given, which validate that the proposed algorithms have obvious performance advantages in terms of the network utility, the hit ratio of the cache, and the quality of service guarantee, and are suitable for the cache-enabled UDN with constrained-backhaul link.
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spelling pubmed-66037762019-07-17 Multi-Location-Aware Joint Optimization of Content Caching and Delivery for Backhaul-Constrained UDN Jing, Wenpeng Wen, Xiangming Lu, Zhaoming Zhang, Haijun Sensors (Basel) Article Mobile edge caching is regarded as a promising way to reduce the backhaul load of the base stations (BSs). However, the capacity of BSs’ cache tends to be small, while mobile users’ content preferences are diverse. Furthermore, both the locations of users and user-BS association are uncertain in wireless networks. All of these pose great challenges on the content caching and content delivery. This paper studies the joint optimization of the content placement and content delivery schemes in the cache-enabled ultra-dense small-cell network (UDN) with constrained-backhaul link. Considering the differences in decision time-scales, the content placement and content delivery are investigated separately, but their interplay is taken into consideration. Firstly, a content placement problem is formulated, where the uncertainty of user-BS association is considered. Specifically, different from the existing works, the specific multi-location request pattern is considered that users tend to send content requests from more than one but limited locations during one day. Secondly, a user-BS association and wireless resources allocation problem is formulated, with the objective of maximizing users’ data rates under the backhaul bandwidth constraint. Due to the non-convex nature of these two problems, the problem transformation and variables relaxation are adopted, which convert the original problems into more tractable forms. Then, based on the convex optimization methods, a content placement algorithm, and a cache-aware user association and resources allocation algorithm are proposed, respectively. Finally, simulation results are given, which validate that the proposed algorithms have obvious performance advantages in terms of the network utility, the hit ratio of the cache, and the quality of service guarantee, and are suitable for the cache-enabled UDN with constrained-backhaul link. MDPI 2019-05-29 /pmc/articles/PMC6603776/ /pubmed/31146353 http://dx.doi.org/10.3390/s19112449 Text en © 2019 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
Jing, Wenpeng
Wen, Xiangming
Lu, Zhaoming
Zhang, Haijun
Multi-Location-Aware Joint Optimization of Content Caching and Delivery for Backhaul-Constrained UDN
title Multi-Location-Aware Joint Optimization of Content Caching and Delivery for Backhaul-Constrained UDN
title_full Multi-Location-Aware Joint Optimization of Content Caching and Delivery for Backhaul-Constrained UDN
title_fullStr Multi-Location-Aware Joint Optimization of Content Caching and Delivery for Backhaul-Constrained UDN
title_full_unstemmed Multi-Location-Aware Joint Optimization of Content Caching and Delivery for Backhaul-Constrained UDN
title_short Multi-Location-Aware Joint Optimization of Content Caching and Delivery for Backhaul-Constrained UDN
title_sort multi-location-aware joint optimization of content caching and delivery for backhaul-constrained udn
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6603776/
https://www.ncbi.nlm.nih.gov/pubmed/31146353
http://dx.doi.org/10.3390/s19112449
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