A Profit-Aware Allocation of High Performance Computing Applications on Distributed Cloud Data Centers with Environmental Considerations

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

Abstract

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 affecting the profit of a cloud provider. In a SGDC, as the data centers are located in different corners of the world, the cost of energy 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 provider'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 demonstrate that the proposed framework enhances the CO2 emission by 17% and the provider's profit by 9% in average.

Keywords

Cloud Computing, Data Center, Energy-Aware Allocation, CO2 Emission, Multi-Objective Optimization, Live Migration