Environment-conscious scheduling of HPC applications on distributed Cloud-oriented data centers

By Saurabh Kumar Garg, Chee Shin Yeo, Arun Anandasivam, Rajkumar Buyya. J. Parallel Distributed Comput., 2011

329 citations recorded by the source corpus.

The use of High Performance Computing (HPC) in commercial and consumer IT applications is becoming popular. HPC users need the ability to gain rapid and scalable access to high-end computing capabilities. Cloud computing promises to deliver such a computing infrastructure using data centers so that HPC users can access applications and data from a Cloud anywhere in the world on demand and pay based on what they use. However, the growing demand drastically increases the energy consumption of data centers, which has become a critical issue. High energy consumption not only translates to high energy cost which will reduce the profit margin of Cloud providers, but also high carbon emissions which are not environmentally sustainable. Hence, there is an urgent need for energy-efficient solutions that can address the high increase in the energy consumption from the perspective of not only the Cloud provider, but also from the environment. To address this issue, we propose near-optimal scheduling policies that exploit heterogeneity across multiple data centers for a Cloud provider. We consider a number of energy efficiency factors (such as energy cost, carbon emission rate, workload, and CPU power efficiency) which change across different data centers depending on their location, architectural design, and management system. Our carbon/energy based scheduling policies are able to achieve on average up to 25% of energy savings in comparison to profit based scheduling policies leading to higher profit and less carbon emissions.

Subfields: Computer Networks and Communications, Hardware and Architecture, Information Systems

View Paper: https://www.semanticscholar.org/paper/82bb26b663c5c6768677c7951ae116fa78bfb081

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

  1. Inderveer Chana
  2. Nidhi Jain Kansal

In Hardware and Architecture

  1. Inderveer Chana
  2. Nidhi Jain Kansal

In Information Systems

  1. Inderveer Chana
  2. Nidhi Jain Kansal

Citations in the corpus