TY - JOUR
T1 - Optimal replication algorithm for scalable streaming media in content delivery networks
AU - Su, Zhou
AU - Katto, Jiro
AU - Yasuda, Yasuhiko
PY - 2004/12
Y1 - 2004/12
N2 - CDN (Content Delivery Networks) improves end-user performance by replicating web contents on a group of geographically distributed servers. However, repeatedly keeping the entire replica of the original objects into many content servers consumes too much server resource. This problem becomes more serious for the large-sized objects such as streaming media, e.g. high quality video. In this paper, we therefore propose an efficient replication method for layered video streams in CDN, which can reduce user response delays and storage costs simultaneously. Based on an analytical formulation of the cooperative replication of layers and segments of each video stream, we derive a replication algorithm which solves next three problems quantitatively. (1) How many servers should be selected to replicate a given video stream? (2) For a single video stream, how many layers and segments should be stored in a given server? (3) After selecting a group of servers for each video stream, how do we allocate the replication priority (i.e. order) to each server? Simulation results verify that the proposed algorithm efficiently resolves the above problems and provides much better performance than conventional methods.
AB - CDN (Content Delivery Networks) improves end-user performance by replicating web contents on a group of geographically distributed servers. However, repeatedly keeping the entire replica of the original objects into many content servers consumes too much server resource. This problem becomes more serious for the large-sized objects such as streaming media, e.g. high quality video. In this paper, we therefore propose an efficient replication method for layered video streams in CDN, which can reduce user response delays and storage costs simultaneously. Based on an analytical formulation of the cooperative replication of layers and segments of each video stream, we derive a replication algorithm which solves next three problems quantitatively. (1) How many servers should be selected to replicate a given video stream? (2) For a single video stream, how many layers and segments should be stored in a given server? (3) After selecting a group of servers for each video stream, how do we allocate the replication priority (i.e. order) to each server? Simulation results verify that the proposed algorithm efficiently resolves the above problems and provides much better performance than conventional methods.
KW - Content delivery networks
KW - Network traffic
KW - Replication algorithm
KW - Scalable video streaming
KW - Web cache performance
UR - http://www.scopus.com/inward/record.url?scp=11144295708&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=11144295708&partnerID=8YFLogxK
M3 - Article
AN - SCOPUS:11144295708
SN - 0916-8532
VL - E87-D
SP - 2723
EP - 2732
JO - IEICE Transactions on Information and Systems
JF - IEICE Transactions on Information and Systems
IS - 12
ER -