Abstract
We are witnessing a considerable amount of research work related to data center and cloud infrastructures but evaluations are often limited to small-scale scenarios as very few researchers have access to a real infrastructure to confront their ideas to reality. We present our experiment automation tool, DiG (Data centers in the Grid), which explicitly allocates physical resources in grids to emulate data center and cloud networks. DiG allows one to utilize grid infrastructures to evaluate research ideas pertaining to data centers and cloud environments at massive scale and with real traffic workload. We have automated the procedure of building target network topologies while respecting available physical resources in the grid against the demand of links and hosts in the experiment. We will present a showcase where DiG automatically builds a large data center topology composed of hundreds of servers executing various Hadoop intensive workloads.
Source Code
The source code of the tool is available at https://github.com/hksoni/DiG.git
Demonstration Videos:
Basic Topology: 5 OpenFlow switches 5 Hosts
Fat-Tree Topology: Fat-Tree 4.
