Name
Abstract | ||
|---|---|---|
Due to the high growth of SNS population, service scalability is one of the critical issues to be addressed. The cloud environment provides the flexible computing and storage resources for services deployment, which fits the characteristics of scalable SNS deployment. However, if the SNS related information is not properly placed, it will cause unbalance load and heavy transmission cost on the storage virtual machine (VM) and cloud data center (CDC) network. In this paper, we characterize the SNS into a graph model based on the users' associations and interest correlations. The node weight represents the degree of associations, which can be indexed by the number of friends or data sources, and the link weight denotes the correlation between users/data sources. Then, based on the SNS graph, the two-step algorithm is proposed in this paper to determine the placement of SNS related data among VMs. Two k-means based clustering schemes are proposed to allocate social data in proper VM and physical servers for pre-configured VM and dynamic VM environment, respectively. The experimental example was conducted and to illustrate and compare the performance of the proposed schemes. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.3837/tiis.2015.08.027 | KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS |
Keywords | Field | DocType |
Social network services,Cloud computing,Virtual machine,Data placement,K-means clustering | Population,k-means clustering,Virtual machine,Software deployment,Computer science,Server,Computer network,Cluster analysis,Cloud computing,Scalability,Distributed computing | Journal |
Volume | Issue | ISSN |
9 | 8 | 1976-7277 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yen-Wen Chen | 1 | 144 | 24.44 |
| Meng-Hsien Lin | 2 | 15 | 4.92 |
| Min-Yan Wu | 3 | 0 | 0.34 |