Presentation Title

Energy Aware Scheduling for Green Cloud Computing

Presenter Information

Anusha KothapallyFollow

Advisor Information

Hesham Ali

Location

Dr. C.C. and Mabel L. Criss Library

Presentation Type

Poster

Start Date

2-3-2018 12:30 PM

End Date

2-3-2018 1:45 PM

Abstract

Energy Aware Scheduling for Green Cloud Computing

Graduate Student: Anusha Kothapally

Supervisor: Hesham Ali

Abstract — Cloud computing is an emerging technology that many IT companies are utilizing since it offers potential benefits to both cloud consumer and cloud owner. It is a new class of network-based computing that takes place over the Internet. While there are many efforts to increase the performance of cloud services, limited reported research has been developed with a focus on energy dissipation. The contemporary single data center would own thousands of servers, which would cause huge power devour. It is reported in one of the surveys that data centers are consuming around 3.5% of the total world’s energy. Energy consumption has become a significant concern for cloud service providers in terms of financial and environmental factors. In this study, we develop a new mechanism that employs the concept of task consolidation to reduce energy consumption in cloud environments. We use multi-layer graphs to model the key factors that need to be considered for task consolidation such as processor speed, process availability, memory requirements, and communication cost among relate tasks. The proposed model can be extended to include other parameters as needed for each computational environment which allows cloud providers to customize their task schedulers according to their own workload profiles. Early results show that the proposed approach leads to significant energy saving for various scenarios of cloud services.

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Mar 2nd, 12:30 PM Mar 2nd, 1:45 PM

Energy Aware Scheduling for Green Cloud Computing

Dr. C.C. and Mabel L. Criss Library

Energy Aware Scheduling for Green Cloud Computing

Graduate Student: Anusha Kothapally

Supervisor: Hesham Ali

Abstract — Cloud computing is an emerging technology that many IT companies are utilizing since it offers potential benefits to both cloud consumer and cloud owner. It is a new class of network-based computing that takes place over the Internet. While there are many efforts to increase the performance of cloud services, limited reported research has been developed with a focus on energy dissipation. The contemporary single data center would own thousands of servers, which would cause huge power devour. It is reported in one of the surveys that data centers are consuming around 3.5% of the total world’s energy. Energy consumption has become a significant concern for cloud service providers in terms of financial and environmental factors. In this study, we develop a new mechanism that employs the concept of task consolidation to reduce energy consumption in cloud environments. We use multi-layer graphs to model the key factors that need to be considered for task consolidation such as processor speed, process availability, memory requirements, and communication cost among relate tasks. The proposed model can be extended to include other parameters as needed for each computational environment which allows cloud providers to customize their task schedulers according to their own workload profiles. Early results show that the proposed approach leads to significant energy saving for various scenarios of cloud services.