This research is based on scheduling jobs on hybrid cloud. Currently we are investigating compute intensive jobs to scheduling on Amazon Web Service(AWS) Spot and On-demand clouds. AWS spot clouds are often cheaper but has additive risk of uninformed failure. The challenge here is to utilize these Spot clouds to reduce cost. Our recent research shows that Amazon Asia Pacific Singapore Data-center and US East Virginia Data-center shows an effective cost savings of over 90% when using spot VMs with more than 95% savings for Small, Medium, Large and Extra-Large general purpose VMs in year 2014. This is highly favorable for cost-conscious enterprises in emerging markets. We are also trying to incorporate strategies like check-pointing, migration, etc. to optimize the trade-off between the cost savings and reliability factors.
We are also working on job scheduling on local clouds. Here we are investigating different type of jobs like I/O intensive, compute intensive, massively parallel jobs, etc. The optimization parameters here are utilization percentage, cost, job completion time etc. Currently we are working with open-stack and trying different scheduling strategies for mapping VM instances to host (physical infrastructure).