Name
Abstract | ||
|---|---|---|
Cloud disaster tolerance has been widely used as a data security mechanism in which multiple replicas of disaster tolerance data are stored in different backup nodes for reliability. In this paper, we deeply study the optimal data backup strategy that backup nodes set the resources prices and source nodes determine the resources quantities that they want to rent. Firstly, we apply a Stackelberg game framework to simulate the interaction among source nodes and backup nodes whose objective is to gain the maximum payoff of every source node and the maximum total payoff of all the backup nodes by adjusting strategies interactively. And then we propose an algorithm to compute the equilibrium price strategy for backup nodes and equilibrium price strategy for source nodes. Finally, we validate this optimal backup strategy through numerical analysis. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/CITS.2016.7546444 | 2016 International Conference on Computer, Information and Telecommunication Systems (CITS) |
Keywords | Field | DocType |
cloud disaster tolerance,data security mechanism,disaster tolerance data,reliability,optimal data backup strategy,source nodes,Stackelberg game framework,maximum total payoff,backup nodes,equilibrium price strategy | Data security,Computer science,Stackelberg competition,Nash equilibrium,Backup,Distributed computing,Cloud computing,Stochastic game | Conference |
ISSN | ISBN | Citations |
2326-2338 | 978-1-5090-0691-5 | 0 |
PageRank | References | Authors |
0.34 | 3 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xu Liu | 1 | 5 | 2.81 |
| Xiaoqiang Di | 2 | 9 | 7.31 |
| Jinqing Li | 3 | 3 | 5.81 |
| Hui Qi | 4 | 3 | 1.38 |
| Huamin Yang | 5 | 19 | 17.29 |
| Ligang Cong | 6 | 5 | 1.79 |