Revenue Maximization for Dynamic Expansion of Geo-Distributed Cloud Data Centers
Abstract
With geographically distributed data centers, it brings better reliability and robustness in the cloud environment. Revenue Maximization for Dynamic Expansion of Geo-distributed Cloud Data Centers As the growth of large-scale applications in geo-distributed cloud systems increases rapidly the resource demand from different areas, and researchers pay more attention by using limited cloud resources to meet the VM demands of as many cloud users as possible. There are, however, many issues in existing works for cloud users, such as denying the VM demands and high response latency.
In this Revenue Maximization for Dynamic Expansion of Geo-Distributed Cloud Data Centers paper, we present a cloud system model for the cloud provider to expand the scale of geo-distributed date centers dynamically.The cloud provider rents hardware resources from other resource owners (ROs) in our model, who have redundant resources and are willing to rent them out.
System Configuration
H/W System Configuration
Speed : 1.1 GHz
RAM : 256 MB(min)
Hard Disk : 20 GB
Floppy Drive : 1.44 MB
Key Board : Standard Windows Keyboard
Mouse : Two or Three Button Mouse
Monitor : SVGA
S/W System Configuration
Platform : cloud computing
Operating system : Windows Xp,7,
Server : WAMP/Apache
Working on : Browser Like Firefox, IE
Conclusion
There are a lot of bad user experiences for cloud users due to the lack of cloud resources and data centers, such as high response latency and refusal of VM requests. In this paper, we investigate the technology of expanding the scale of geo-distributed clouds dynamically. First, we propose a cloud system model in which the cloud provider provides hardware resources from other resource owners (ROs), who have redundant resources and are willing to lease them. To maximize cloud system revenue, we define two problems of expanding geo-distributed clouds (EGC) with two service modes, including revenue-oriented and service-oriented.
