Paper Info
Title
Adaptive Data Placement for Improving Performance of Online Social Network Services in a Multicloud Environment
Abstract
AbstractThe existing online social network (OSN) services in a multiple-cloud (Multicloud) environment use replications to store user data for improving the service performance. However, it not only generates tremendous traffic for synchronization between data but also stores considerable redundant data, thus causing large storage costs. In addition, it does not provide dynamic load balancing considering the resource status of each cloud. As a result, it cannot cope with the degradation of performance caused by the resource contention. We introduce an adaptive data placement algorithm without the replications for improving the performance of the OSN services in the Multicloud environment. Our approach is designed to avoid server overhead using data balancing technique, which locates data from a cloud to another according to the amount of traffic. To provide acceptable latency delay, it also considers the relationship between users and the distance between user and cloud when transferring data. To validate our approach, we experimented with actual users’ locations and times of use collected from OSN services. Our findings indicate that this approach can reduce the resource contention by an average of more than 59%, reduce storage volume to at least 50%, and maintain the latency delay under 50 ms.
Year
DOI
Venue
2017
10.1155/2017/2824782
Periodicals
Field
DocType
Volume
Synchronization,Social network,Latency (engineering),Resource contention,Computer science,Computer network,Dynamic load balancing,Cloud computing,Distributed computing
Journal
2017
Issue
ISSN
Citations 
1
1058-9244
1
PageRank 
References 
Authors
0.35
6
5
Name
Order
Citations
PageRank
Seunghee Han110.35
Bo-Sung Kim220.71
Jaemin Han310.35
Kyehee Kim410.35
JooSeok Song530658.82