A Profit-aware Allocation of High Performance Computing Applications on Distributed Cloud Data Centers with Environmental Considerations
Hamid Reza Faragardi, Aboozar Rajabi, Thomas Nolte, Amir Hossein Heidarizadeh · 2014
A Set of Geographically Distributed Cloud data centers (SGDC) is a promising platform to run a large number of High Performance Computing Applications (HPCAs) in a cost-efficient manner. Energy consumption is a key factor affect- ing the profit of a cloud provider. In a SGDC, as the data centers are located in different corners of the world, the cost of en- ergy consumption and the amount of CO2 emission significantly vary among the data centers. Therefore, in such systems not only a proper allocation of HPCAs results in CO2 emission reduction, but it also causes a substantial increase of the provid- er's profit. Furthermore, CO2 emission reduction mitigates the destructive environmental impacts. In this paper, the problem of allocation of a set of HPCAs on a SGDC is discussed where a two-level allocation framework is introduced to deal with the problem. The proposed framework is able to reach a good compromise between CO2 emission and the providers' profit subject to satisfy HPCAs deadlines and memory constraints. Simulation results based on a real intensive workload demon- strate that the proposed framework enhances the CO2 emission by 17% and the provider's profit by 9% in average.