The Toronto Intelligent Decision Engineering Laboratory
Resource Scheduling in Cloud Computing Environments

Resource Scheduling Cloud Computing Environements


Members

J. Christopher Beck
Douglas G. Down
Daria Terekhov
Tony T. Tran

Project description

Cloud computing provides end-users with computing as a service. Notable companies such as Amazon, Google, Verizon, IBM, and Microsoft run and maintain large scale clouds. End-users are able to make use of the computational resources, storage, software, and/or data access on a cloud without knowledge of the details about the machine(s) providing service. By using a cloud, a user is easily able to scale their computational requirements to meet their specific needs.

The management of a cloud leaves providers with the difficult task of dynamically provisioning a large-scale system to meet customers demands. Traditional optimization techniques can not properly handle the scale of the leading cloud environments. Our research examines stochastic optimization strategies which are scalable to the large systems commonly found in clouds to optimize utilization of available servers and improve the timely service of customer requests.


Start date

February 1st, 2011

Funding

University of Toronto, Fellowship
Google Research Grant

Publications

  1. Tran, T.T., & J. C. Beck. "Report: Google Data Center Scheduling", Technical Report, University of Toronto, Canada, 2012.


University of Toronto Mechanical and Information Engineering