Optimizing Energy Consumption with Task Consolidation in Clouds

Hsu, Ching‐Hsien; Slagter, Kenn; Chen, Shih-Chang; Chung, Yeh-Ching

doi:10.1016/j.ins.2012.10.041

Cited by 136 publications

(59 citation statements)

References 14 publications

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“…The unreliable and dynamic requests got to be compelled to run on cloud resources across the net. The resource is unbelievably necessary as one thing like central processing unit, memory, storage, and information measure associated application is usually termed an information and communication technology resource at intervals the cloud surroundings [14]. The matter of resource allocation is quite expensive and desires some assumptions along with a set of workflow tasks for resource requirements, set of working servers, task consolidation meeting service level agreement, and reduction in power wastage and resource usage costs.…”

Section: Related Workmentioning

confidence: 99%

Energy Saving from Cloud Resourcesfor a Sustainable Green Cloud ComputingEnvironment

Karuppasamy

Balakannan

2018

JCSM

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Cloud computing services are proliferation. The Cloud computing resources face major pitfall in energy consumes. The prime of energy consumption in cloud computing is by means of client computational devices, server computational devices, network computational devices and power required to cool the IT load. The cloud resources contribute high operational energy cost and emit more carbon emission to the environment. Therefore the cloud services providers need green cloud environment resolution to decrease the operational energy cost along with environmental impact. The most important objective of this effort is to trim down the energy from utilized and unutilized (idle) cloud resources and save the energy in cloud resources efficiently. To achieve the sustainable green cloud environment from an Energy Saving Algorithm used to choose the appropriate virtual services so that the power at the client, server, and network recourses can be reduced.

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Section: Related Workmentioning

confidence: 99%

Energy Saving from Cloud Resourcesfor a Sustainable Green Cloud ComputingEnvironment

Karuppasamy

Balakannan

2018

JCSM

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“…Similarly, resource consolidation moves the servers around to reduce the number of active resources and can switch off some underutilized resources to save the resource idle energy. Load balancing [30] attempts to distribute the load across different servers that can be achieved through server consolidation in clouds and task consolidation [31] in clusters and grids. Load balancing can increase the servers utilization level, and can possibly minimize the total energy consumption.…”

Section: Cooling Systems Including Computer Room Air Conditioning Unimentioning

confidence: 99%

“…Load balancing can increase the servers utilization level, and can possibly minimize the total energy consumption. However, increasing the resource utilization does not always result in minimum energy consumption due to workload variations [31], hence an Energy-aware Task Consolidation (ETC) method is proposed in [31] to restrict the CPU usage below a specific threshold value. Estimating such a threshold level for a server in clouds, where the demand varies over time, is a challenging task due to workload unpredictability and heterogeneity.…”

Section: Cooling Systems Including Computer Room Air Conditioning Unimentioning

confidence: 99%

Energy efficient computing, clusters, grids and clouds: A taxonomy and survey

Zakarya

Gillam

2017

Sustainable Computing: Informatics and Systems

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“…Ching-Hsien Hsu et al [11] have developed a technique that reduces energy consumption is energy-aware task consolidation (ETC) technique. ETC restricts CPU use below a specified peak threshold.…”

Section: Energy-aware Task Consolidationmentioning

confidence: 99%