SLA-Aware Energy Efficient Resource Management for Cloud Environments

Mustafa, Saad; Bilal, Kashif; Malik, Saif Ur Rehman; Madani, Sajjad A.

doi:10.1109/access.2018.2808320

Cited by 43 publications

(27 citation statements)

References 41 publications

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“…erefore, the quality of the multitenant based service system can be guaranteed. Mustafa et al [14] leveraged the notion of workload consolidation to improve energy efficiency by putting incoming jobs on as few servers as possible. e concept of SLA is also imported to minimize the total SLA violations.…”

Section: Qos Optimization and Energy Saving Techniques In Different Cmentioning

confidence: 99%

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Study QoS Optimization and Energy Saving Techniques in Cloud, Fog, Edge, and IoT

Wang

Sun

et al. 2020

Complexity

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With an increase of service users’ demands on high quality of services (QoS), more and more efficient service computing models are proposed. The development of cloud computing, fog computing, and edge computing brings a number of challenges, e.g., QoS optimization and energy saving. We do a comprehensive survey on QoS optimization and energy saving in cloud computing, fog computing, edge computing, and IoT environments. We summarize the main challenges and analyze corresponding solutions proposed by existing works. This survey aims to help readers have a deeper understanding on the concepts of different computing models and study the techniques of QoS optimization and energy saving in these models.

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Section: Qos Optimization and Energy Saving Techniques In Different Cmentioning

confidence: 99%

“…Given that a change in workload changes the utilization of CPU required over time. So, an integral function (formula (2) [14]) is used to represent the total energy (E) consumed by a server (S) operation:…”

Section: Qos Optimization and Energy Saving Techniques In Different Cmentioning

confidence: 99%

Study QoS Optimization and Energy Saving Techniques in Cloud, Fog, Edge, and IoT

Wang

Sun

et al. 2020

Complexity

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“…Upgraded two existing methods is by improving the energy productivity and presenting SLA attention to minimize the general SLA infringement. Execution assessment of the strategies is done dependent on fluctuating workloads and systems beat existing methods as far as energy productivity, SLA consistence and performance affirmation [4]. They examine a coordinated, energy consumption, resource assignments for overcommitted cloud environment.…”

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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“…at some point of this undertaking execution productivity of server farms are completed and flexibility is advanced. Mustafa, S et al [15] had been provided calculations named available ability and strength (ACP) and Required capability and electricity (RCP) through which a server is desired for the bottom of open CPU functionality and the power that mght be expended for that limit. while utilising the verifiable data and wisely substituting the estimations of the facts relying on changing and difficult to understand last obligations reachable, it supported to perform dynamic VM solidification.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The forecast of software is achieved right here through utilizing direct relapse method. The capability exhibited the direct affiliation a few of the up and coming and present CPU usage of each single hosts are as following: (15) where, β 0 and β 1 are regression coefficient constraints that calculate in accordance with the r previous CPU utilization in a physical host. The is the predicted or estimated value of the CPU utilization; is the predictor which gives current CPU utilization value.…”

Section: Upper Threshold Calculationmentioning

confidence: 99%

A Heuristic Research of the Designing and Evaluation of Energy Efficiency using Dynamic VM Consolidation in Green Cloud Data Centres

2019

IJITEE

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Allotted computing is a blasting innovation that tenders effective assets, and smooth accessibility through web based processing. however, the growing wishes of clients for such administrations are convincing the cloud professional corporations to send huge portions of strength hungry server farms which element awful effect to the earth with the aid of the usage of plenteous Carbon Dioxide discharge. To limit control usage and strengthen the quality of service (QoS) inside the server farm assesses the strength usage in an assortment of plans in IaaS of dispensed computing situation. Dynamic Virtual Machines’ Consolidation and Placement(DVMCP) is an in a position strategies for enhancing using assets and proficient power usage in Cloud DataCenters. in this exploration, we proposed a calculation, Energy Conscious Greeny Cloud Dynamic (ECGCD) set of rules that accomplishes live VM relocation that is turning off the inert has or located it to lowcontrol mode (i.e., rest or hibernation),that builds up power productivity and succesful usage of property in the dynamic hosts. The take a look at stop result confirmations with duplicate that, the proposed calculation achieves good sized diploma of lower in electricity usage in correlation with the modern-day-day VM combination calculations.

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SLA-Aware Energy Efficient Resource Management for Cloud Environments

Cited by 43 publications

References 41 publications

Study QoS Optimization and Energy Saving Techniques in Cloud, Fog, Edge, and IoT

Study QoS Optimization and Energy Saving Techniques in Cloud, Fog, Edge, and IoT

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

A Heuristic Research of the Designing and Evaluation of Energy Efficiency using Dynamic VM Consolidation in Green Cloud Data Centres

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