Joint Replica Server Placement, Content Caching, and Request Load Assignment in Content Delivery Networks

With the explosive growth of information and communication technology and its services, some popular Websites currently generate an enormous amount of Internet traffic. A content delivery network (CDN) would then become imperative for supporting such services efficiently. In this paper, we propose j...

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Main Authors: Kai Xu, Xiang Li, Sanjay Kumar Bose, Gangxiang Shen
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8320783/
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spelling doaj-d5ec061e9f07408abae1768adbcc74252021-03-29T21:00:12ZengIEEEIEEE Access2169-35362018-01-016179681798110.1109/ACCESS.2018.28176468320783Joint Replica Server Placement, Content Caching, and Request Load Assignment in Content Delivery NetworksKai Xu0Xiang Li1Sanjay Kumar Bose2Gangxiang Shen3https://orcid.org/0000-0002-7342-6980School 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, ChinaWith the explosive growth of information and communication technology and its services, some popular Websites currently generate an enormous amount of Internet traffic. A content delivery network (CDN) would then become imperative for supporting such services efficiently. In this paper, we propose joint optimizing approaches for replica server placement, content caching in selected servers, and content request load assignment among the servers, aiming to minimize the ratio of unserved content request load when the network resources and server capacity are both limited. For this, we develop a mixed integer linear programming (MILP) optimization model. To mitigate the computational complexity of the MILP model, we further decompose the optimization problem into three sub-problems, including: 1) choosing the replica server nodes optimally; 2) deciding the content items to be cached in the replica servers; and 3) allocating the content request loads from users onto different servers. For these sub-problems, we develop corresponding heuristic algorithms and show that the proposed approach is not only efficient but also performs very close to the MILP model. We also find that a number of system limitations, such as different numbers of replica servers placed, link capacity, server processing capacity, and server storage capacity, jointly affect the performance of the CDN. Saturation trends are observed on the performance, which indicate that as long as sufficient resources have already been provided, augmenting the resources further may only lead to marginal additional performance improvement.https://ieeexplore.ieee.org/document/8320783/Content delivery networkreplica server placementcontent cachingnetwork resource allocation
collection DOAJ
language English
format Article
sources DOAJ
author Kai Xu
Xiang Li
Sanjay Kumar Bose
Gangxiang Shen
spellingShingle Kai Xu
Xiang Li
Sanjay Kumar Bose
Gangxiang Shen
Joint Replica Server Placement, Content Caching, and Request Load Assignment in Content Delivery Networks
IEEE Access
Content delivery network
replica server placement
content caching
network resource allocation
author_facet Kai Xu
Xiang Li
Sanjay Kumar Bose
Gangxiang Shen
author_sort Kai Xu
title Joint Replica Server Placement, Content Caching, and Request Load Assignment in Content Delivery Networks
title_short Joint Replica Server Placement, Content Caching, and Request Load Assignment in Content Delivery Networks
title_full Joint Replica Server Placement, Content Caching, and Request Load Assignment in Content Delivery Networks
title_fullStr Joint Replica Server Placement, Content Caching, and Request Load Assignment in Content Delivery Networks
title_full_unstemmed Joint Replica Server Placement, Content Caching, and Request Load Assignment in Content Delivery Networks
title_sort joint replica server placement, content caching, and request load assignment in content delivery networks
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2018-01-01
description With the explosive growth of information and communication technology and its services, some popular Websites currently generate an enormous amount of Internet traffic. A content delivery network (CDN) would then become imperative for supporting such services efficiently. In this paper, we propose joint optimizing approaches for replica server placement, content caching in selected servers, and content request load assignment among the servers, aiming to minimize the ratio of unserved content request load when the network resources and server capacity are both limited. For this, we develop a mixed integer linear programming (MILP) optimization model. To mitigate the computational complexity of the MILP model, we further decompose the optimization problem into three sub-problems, including: 1) choosing the replica server nodes optimally; 2) deciding the content items to be cached in the replica servers; and 3) allocating the content request loads from users onto different servers. For these sub-problems, we develop corresponding heuristic algorithms and show that the proposed approach is not only efficient but also performs very close to the MILP model. We also find that a number of system limitations, such as different numbers of replica servers placed, link capacity, server processing capacity, and server storage capacity, jointly affect the performance of the CDN. Saturation trends are observed on the performance, which indicate that as long as sufficient resources have already been provided, augmenting the resources further may only lead to marginal additional performance improvement.
topic Content delivery network
replica server placement
content caching
network resource allocation
url https://ieeexplore.ieee.org/document/8320783/
work_keys_str_mv AT kaixu jointreplicaserverplacementcontentcachingandrequestloadassignmentincontentdeliverynetworks
AT xiangli jointreplicaserverplacementcontentcachingandrequestloadassignmentincontentdeliverynetworks
AT sanjaykumarbose jointreplicaserverplacementcontentcachingandrequestloadassignmentincontentdeliverynetworks
AT gangxiangshen jointreplicaserverplacementcontentcachingandrequestloadassignmentincontentdeliverynetworks
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