Green Data Center with Virtualization and Cloud Computing Technique
Green Data Center with Virtualization and Cloud Computing Technique
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Nowadays, reducing the power consumed by large-scale data centers is most concerned issue in several large enterprises. Most of them have a number of servers situated in all branches providing online services. This consumes large amount of power for maintaining and cooling. Virtualization is a promising approach to consolidating multiple online services into a smaller number of computing resources. A virtualized server environment allows computing resources to be shared among multiple performance-isolated platforms called virtual machines. This will allow data center operators to maintain the desired performance while achieving higher server utilization and energy efficiency. For the server part, we implement dynamic management algorithm (DMA). From this, Virtual Machines are ordered according to their migration costs within each Physical Machine. For application part, we adopt cloud computing concept to implement applications providing service to both internal and external stakeholder. To test the system, we implement workload generator to produce workload to the system and measure the performance of the system. By doing this, the enterprise can reduce the cost for maintain servers and provide better service for the staffs and customers effectively.
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1. INTRODUCTION
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Green computing or green IT, refers to environmentally sustainable computing or IT. It is the study and practice of designing, manufacturing, using, and disposing of computers, servers, and associated subsystems—such as monitors, printers, storage devices, and networking and communications systems—efficiently and effectively with minimal or no impact on the environment. Green IT also strives
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Nowadays, reducing the power consumed by large-scale data centers is most concerned issue in several large enterprises. Most of them have a number of servers situated in all branches providing online services. This consumes large amount of power for maintaining and cooling. Virtualization is a promising approach to consolidating multiple online services into a smaller number of computing resources. A virtualized server environment allows computing resources to be shared among multiple performance-isolated platforms called virtual machines. This will allow data center operators to maintain the desired performance while achieving higher server utilization and energy efficiency. For the server part, we implement dynamic management algorithm (DMA). From this, Virtual Machines are ordered according to their migration costs within each Physical Machine. For application part, we adopt cloud computing concept to implement applications providing service to both internal and external stakeholder. To test the system, we implement workload generator to produce workload to the system and measure the performance of the system. By doing this, the enterprise can reduce the cost for maintain servers and provide better service for the staffs and customers effectively.
________________________________________________________________________
1. INTRODUCTION
_________________________________________________________________________________________
Green computing or green IT, refers to environmentally sustainable computing or IT. It is the study and practice of designing, manufacturing, using, and disposing of computers, servers, and associated subsystems—such as monitors, printers, storage devices, and networking and communications systems—efficiently and effectively with minimal or no impact on the environment. Green IT also strives
References: Gunjan Khanna and Kirk Beaty, Gautam Kar, Andrzej Kochut, 2006. Application Performance Management in Virtualized Server Environments. , 373-381. www.phdcomputing.net, “Understanding Cloud Computing”, IEEE Transactions on Semiconductor Manufacturing Industry, August 10, 2009. Liting Hu, Hai Jin, Xiaofei Liao, Xianjie Xiong, Haikun Liu, 2008. Magnet: A Novel Scheduling Policy for Power Reduction in Cluster with Virtual Machines. In IEEE Proceedings of the International Conference on Cluster Computing, 13-22.