Exploiting user provided information in dynamic consolidation of virtual machines to minimize energy consumption of cloud data centers

Khan, Anit; Paplinski, Andrew Peter; Khan, Abdul Malik; Murshed, Manzur; Buyya, Rajkumar

doi:10.1109/fmec.2018.8364052

Cited by 19 publications

(14 citation statements)

References 12 publications

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“…Anit Khan et al [7] discussed about Dynamic consolidation of Virtual Machines (VMs).They proposed a novel heuristic Dynamic VM Consolidation algorithm, RTDVMC, which minimizes the energy consumption of CDC through exploiting CSU provided information.…”

Section: International Journal Of Engineering Research and Technology (mentioning

confidence: 99%

Secure Protected Live Migration for Energy Efficient Techniques

Deep¹

2020

IJERT

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In cloud data centre the VM scheduling technique is used to realize the energy efficient operation of servers and VM migration techniques provides multiple benefits such as resource distribution and energy aware consolidation. In VM migration while moving a task from one VM to another has various security threats. The security is more important during migration to protect the data from the hackers. In the proposed paper, illustrates the security features of energy efficient techniques when it performs live VM migration is the most vulnerable process in cloud for loss of data integrity, confidentiality, unauthorized access and authorization. In this paper we propose a secure energy aware provisioning for data centre resources on virtualized platforms. Energy efficient is achieved through VM scheduling, migration mechanism and ability to switch off resources of the physical machine that are not required by VM. Further we proposed solutions to security challenges occur during VM live migration. The implementation and verification of the proposed technique is evaluated using Cloudsim. The experimental results show that our approach reduces energy consumption in data centres.

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Section: International Journal Of Engineering Research and Technology (mentioning

confidence: 99%

Secure Protected Live Migration for Energy Efficient Techniques

Deep¹

2020

IJERT

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“…This procedure can increment assignments in a host and system while as yet giving enough resources to overcome SLA infringement and resource proportion dependent on the authentic checking information from the online examination of the host and system usage with no pre-learning of remaining loads [6]. VMs are progressively merged dependent on when a VM can be expelled from datacenters helpful data to be gotten from particular user, at that point increasingly physical machines can be transformed into rest state, yielding lower energy utilization [7].…”

Section: Related Workmentioning

confidence: 99%

Dynamic Consolidation of VM Allocation and VM Migration to Optimize Energy Consumption of Cloud Data Centers

Kumar¹,

Kumar²

2019

IJEAT

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Including the expanding fame of the cloud model and quick multiplication of cloud frameworks there are expanding concerns about energy utilization and subsequent effect of cloud as a supporter of worldwide CO2 discharges. Until now, little is thought about how to fuse energy utilization and CO2 worries into cloud application. Energy consumption has become an important cost factor for computing resources. In this research article, we proposed an algorithm to VM Allocation and VM migrations in the context of power utilisation in the data centers. This mechanism is to minimize the energy utilization in the cloud computing environment. We validate our results with the help of prediction based faster energy efficient VMs approach and modified Best Fit approach which shows the faster assignments and increase the performance when consumption of the energy is optimised. As well as we also simulate our results in the cloudsim in the multiple numbers of host and virtual machine to reduce the energy consumptions.

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“…The framework of VM consolidation makes use of package creation algorithms, monitoring the resources and also performing the balanced approach for utilization of CPUs [17]. The K-means method helps in providing VM consolidation and is very helpful for a dynamic environment [18]. Monitoring is one of the important tasks in production environments and to reduce the amount of power the number of instances used for VMs must be reduced.…”

Section: Introductionmentioning

confidence: 99%

“…Monitoring is one of the important tasks in production environments and to reduce the amount of power the number of instances used for VMs must be reduced. When the VMs which exhibit similar behavior characteristics are combined then amount of time required for monitoring can be reduced [18].In order to reduce the operating cost the consolidation of VMs must be performed because it helps in reducing the cost required. The VM consolidation process is automated in order to assign the servers in an adaptive fashion with the objective of power cost and network cost reduction.…”

Section: Introductionmentioning

confidence: 99%

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Virtual Machine Consolidation Method with Low Delay and Energy Consumption Parameters

Nayana¹

2019

IJCA

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There is huge amount of information available and maintaining such a data will require lot of computational power and the solution for these issues is to provide a system with more flexible, reliable and scalable characters. Cloud based orchestration services support the users any time and also can be scaled based on the demand for resources. Demand and delay are directly proportional to each other and if the duration of the delay is exponential then the cost also is also exponential. Performing a balance act between the quality of service and energy consumption rate is proposed by the algorithm. Each of the data center used in the cloud have set of virtual machines. In order have better processing of data consolidation of virtual machines is done. The proposed method is built on a fuzzy logic with consolidation framework. The method filters the virtual machine from an overloaded host and the migration control mechanism build into the system helps in increasing the performance for the selection process. Three characteristics namely mean, standard deviation and media are taken to compute the overload ratio due the selection process to improve optimization.

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Exploiting user provided information in dynamic consolidation of virtual machines to minimize energy consumption of cloud data centers

Cited by 19 publications

References 12 publications

Secure Protected Live Migration for Energy Efficient Techniques

Secure Protected Live Migration for Energy Efficient Techniques

Dynamic Consolidation of VM Allocation and VM Migration to Optimize Energy Consumption of Cloud Data Centers

Virtual Machine Consolidation Method with Low Delay and Energy Consumption Parameters

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