Zone-Based Cooperative Content Caching and Delivery for Radio Access Network With Mobile Edge Computing

Mobile edge computing (MEC) is a promising solution to meet the latency requirement for delay-sensitive services in a 5G radio access network (RAN). Its key idea is to deploy computing and storage capacities at the edge of the RAN to quickly provision content and processing capacities as required by...

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Main Authors: Ning Wang, Gangxiang Shen, Sanjay Kumar Bose, Weidong Shao
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8581499/
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spelling doaj-484211a2f8e64f3e9943e9c5ae80d7362021-03-29T22:09:34ZengIEEEIEEE Access2169-35362019-01-0174031404410.1109/ACCESS.2018.28886028581499Zone-Based Cooperative Content Caching and Delivery for Radio Access Network With Mobile Edge ComputingNing Wang0Gangxiang Shen1https://orcid.org/0000-0002-7342-6980Sanjay Kumar Bose2Weidong Shao3School of Electronic and Information Engineering, Soochow University, Suzhou, ChinaSchool of Electronic and Information Engineering, Soochow University, Suzhou, ChinaDepartment of EEE, IIT Guwahati, Guwahati, IndiaSchool of Electronic and Information Engineering, Soochow University, Suzhou, ChinaMobile edge computing (MEC) is a promising solution to meet the latency requirement for delay-sensitive services in a 5G radio access network (RAN). Its key idea is to deploy computing and storage capacities at the edge of the RAN to quickly provision content and processing capacities as required by the users. Efficient content caching and delivery are key issues to ensure the success of this technique. This paper proposes a zone-based cooperative content caching and delivery scheme for a RAN supporting MEC (MEC-RAN), where the RAN is modelled as a zone and is further sub-divided into multiple sub-zones. Content items are cooperatively cached and delivered among multiple sub-zones. The caching problem is formulated as a mixed integer linear programming model. We also develop a heuristic cooperative content caching strategy to decide the content items to be cached in each MEC server. This novel strategy divides the storage space in each MEC server into two parts. The first part caches locally popular contents and the second part is used to cooperatively cache zone-wide popular items. We study the proposed scheme both through simulations and implementation on a testbed that consists of a subnetwork on our campus and commercial cloud service from Ali-Cloud. Both of these show that the proposed zone-based scheme performs better than other typical caching strategies in terms of average content delivery latency and balanced loading of the MEC servers.https://ieeexplore.ieee.org/document/8581499/Content delivery networkmobile edge computingoptimal caching strategyzone-based cooperative content caching
collection DOAJ
language English
format Article
sources DOAJ
author Ning Wang
Gangxiang Shen
Sanjay Kumar Bose
Weidong Shao
spellingShingle Ning Wang
Gangxiang Shen
Sanjay Kumar Bose
Weidong Shao
Zone-Based Cooperative Content Caching and Delivery for Radio Access Network With Mobile Edge Computing
IEEE Access
Content delivery network
mobile edge computing
optimal caching strategy
zone-based cooperative content caching
author_facet Ning Wang
Gangxiang Shen
Sanjay Kumar Bose
Weidong Shao
author_sort Ning Wang
title Zone-Based Cooperative Content Caching and Delivery for Radio Access Network With Mobile Edge Computing
title_short Zone-Based Cooperative Content Caching and Delivery for Radio Access Network With Mobile Edge Computing
title_full Zone-Based Cooperative Content Caching and Delivery for Radio Access Network With Mobile Edge Computing
title_fullStr Zone-Based Cooperative Content Caching and Delivery for Radio Access Network With Mobile Edge Computing
title_full_unstemmed Zone-Based Cooperative Content Caching and Delivery for Radio Access Network With Mobile Edge Computing
title_sort zone-based cooperative content caching and delivery for radio access network with mobile edge computing
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2019-01-01
description Mobile edge computing (MEC) is a promising solution to meet the latency requirement for delay-sensitive services in a 5G radio access network (RAN). Its key idea is to deploy computing and storage capacities at the edge of the RAN to quickly provision content and processing capacities as required by the users. Efficient content caching and delivery are key issues to ensure the success of this technique. This paper proposes a zone-based cooperative content caching and delivery scheme for a RAN supporting MEC (MEC-RAN), where the RAN is modelled as a zone and is further sub-divided into multiple sub-zones. Content items are cooperatively cached and delivered among multiple sub-zones. The caching problem is formulated as a mixed integer linear programming model. We also develop a heuristic cooperative content caching strategy to decide the content items to be cached in each MEC server. This novel strategy divides the storage space in each MEC server into two parts. The first part caches locally popular contents and the second part is used to cooperatively cache zone-wide popular items. We study the proposed scheme both through simulations and implementation on a testbed that consists of a subnetwork on our campus and commercial cloud service from Ali-Cloud. Both of these show that the proposed zone-based scheme performs better than other typical caching strategies in terms of average content delivery latency and balanced loading of the MEC servers.
topic Content delivery network
mobile edge computing
optimal caching strategy
zone-based cooperative content caching
url https://ieeexplore.ieee.org/document/8581499/
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AT gangxiangshen zonebasedcooperativecontentcachinganddeliveryforradioaccessnetworkwithmobileedgecomputing
AT sanjaykumarbose zonebasedcooperativecontentcachinganddeliveryforradioaccessnetworkwithmobileedgecomputing
AT weidongshao zonebasedcooperativecontentcachinganddeliveryforradioaccessnetworkwithmobileedgecomputing
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