Green Power Management with Dynamic Resource Allocation for Cloud Virtual Machines

Yang, Chao-Tung; Wang, Kuan-Chieh; Cheng, Hsiang-Yao; Kuo, Cheng-Ta; Chu, William C.

doi:10.1109/hpcc.2011.103

Cited by 23 publications

(14 citation statements)

References 24 publications

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“…In spite of our approach the used utility function and capacity planning method are not using noninfrastructure metrics. A lot of recent work deals with computing resource allocation in clouds, focusing on specific management objectives, such as energy efficiency [9], fairness [10], economic fitness [11], and service differentiation [12]. All of the above works however deliver placement solutions.…”

Section: Related Workmentioning

confidence: 99%

Cloud QoS Scaling by Fuzzy Logic

Frey

Lüthje

Reich

et al. 2014

2014 IEEE International Conference on Cloud Engineering

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One of the biggest advantages of cloud infrastructures is the elasticity. Cloud services are monitored and based on the resource utilization and performance load, they get scaled up or down, by provision or deprovision of cloud resources. The goal is to guarantee the customers an acceptable performance with a minimum of resources. Such Quality of Service (QoS) characteristics are stated in a contract, called Service Level Agreement (SLA) negotiated between customer and provider. The approach of this paper shows that with additional imprecise information (e.g. expected daytime/weektime performance) modeled with fuzzy logic and used in a behavior, load and performance prediction model, the up and down scaling mechanism of a cloud service can be optimized. Evaluation results confirm, that using this approach, SLA violation can be minimized.

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Section: Related Workmentioning

confidence: 99%

Cloud QoS Scaling by Fuzzy Logic

Frey

Lüthje

Reich

et al. 2014

2014 IEEE International Conference on Cloud Engineering

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“…Other route for decreasing the power utilization is to diminish the CPU use and other sit still resources. The statistics say that even with 10% of CPU usage, the total power utilization came to up to 50% at the peak [5].…”

Section: Introductionmentioning

confidence: 99%

Towards Energy Efficient Cloud Computing Using Dependency Graph

Sahu¹,

Verma²

2019

IJCET

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Nowadays, research are being directed in the field of large system models. These large system models generally manages the distributed environment to break down and understand behavior of the systems. A large number of the system give simulation of the distributed environment to run their experiments. Hence, when there is an expansion in demand of cloud and distributed system, side by side it is important to maintain the power consumption and efficiency of the framework. This is a most challenging assignment to perform. In this paper, we give energy optimizing model with the help of migration manager to manage the productivity of the entire system. We will contrast DVFS algorithm with on Demand and Conservative mode of operation in cloud. We will exhibit our experiment in CloudSim software.

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“…Another way of reducing the power consumption is to reduce the CPU utilization and other idle resources. Even with 10% CPU utilization, the total power consumption is more than 50% at the peak [2].…”

Section: Introductionmentioning

confidence: 99%

Efficient energy consumption in green cloud

Valliyammai

Uma

et al. 2014

2014 International Conference on Recent Trends in Information Technology

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In the field of cloud computing, energy efficiency plays a major role. This is because the usage of cloud is increasing and so is the cost of energy; and also there is a necessity to reduce the carbon emission which occurs due to the usage of information and communication technologies (ICT). Hence there is a need for energy-efficient technologies that should reduce the overall energy consumption that is needed for computation, storage and communications. The proposed mechanism reduces the energy consumption by suspending the idle virtual machines (VMs) and categorizing the active VMs into different energy clusters with the help of fuzzy C-means algorithm. Also the percentage of Service Level Agreement (SLA) violated is kept minimal.

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Green Power Management with Dynamic Resource Allocation for Cloud Virtual Machines

Cited by 23 publications

References 24 publications

Cloud QoS Scaling by Fuzzy Logic

Cloud QoS Scaling by Fuzzy Logic

Towards Energy Efficient Cloud Computing Using Dependency Graph

Efficient energy consumption in green cloud

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