Simulator improvements to validate the Green Cloud Computing approach

Werner, Jorge; Gerônimo, Guilherme Arthur; Westphall, Carlos Becker; Koch, Fernando; Freitas, Rafael

doi:10.1109/lanoms.2011.6102263

Cited by 15 publications

(15 citation statements)

References 8 publications

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“…Considering the theory and practice of network management policies in [44], which also encompasses the DVFS, DNS and DPM methodologies, the findings of this study suggest the following:…”

Section: Discussionmentioning

confidence: 96%

On energy consumption of switch-centric data center networks

Popoola

Pranggono

2017

J Supercomput

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Data center network (DCN) is the core of cloud computing and accounts for 40% energy spend when compared to cooling system, power distribution and conversion of the whole data center (DC) facility. It is essential to reduce the energy consumption of DCN to ensure energy-efficient (green) data center can be achieved. An analysis of DC performance and efficiency emphasizing the effect of bandwidth provisioning and throughput on energy proportionality of two most common switchcentric DCN topologies: three-tier (3T) and fat tree (FT) based on the amount of actual energy that is turned into computing power are presented. Energy consumption of switch-centric DCNs by realistic simulations is analyzed using GreenCloud simulator. Power-related metrics were derived and adapted for the information technology equipment processes within the DCN. These metrics are acknowledged as subset of the major metrics of power usage effectiveness and data center infrastructure efficiency, known to DCs. This study suggests that although in overall FT consumes more energy, it spends less energy for transmission of a single bit of information, outperforming 3T.

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“…Considering the theory and practice of network management policies in [44], which also encompasses the DVFS, DNS and DPM methodologies, the findings of this study suggest the following:…”

Section: Discussionmentioning

confidence: 96%

On energy consumption of switch-centric data center networks

Popoola

Pranggono

2017

J Supercomput

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“…Hence, a multi-agent simulation approach (e.g. similar to the presented in [34]) could be considered for spot cloud modeling. However, Amazon has published very little information regarding construction of the spot market (e.g.…”

Section: Discussionmentioning

confidence: 99%

On optimization of simulation execution on Amazon EC2 spot market

Kamiński

Szufel

2015

Simulation Modelling Practice and Theory

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a b s t r a c tLarge scale simulations require considerable amounts of computing power and often cloud services are utilized to perform them. In such settings the execution costs can be significantly decreased through the use of the Amazon spot price market. Its downside is that Amazon can interrupt the user's computations when her bid price is too low. This poses a problem in finding an on-line bidding algorithm that balances the computation cost and the simulation experiment completion time.We identify key drivers governing the spot prices on Amazon EC2 and using these insights propose an adaptive bidding strategy that simultaneously minimizes the computation cost and the delays due to computation termination. We show that bidding close to a spot price and dynamically switching between instances is a strategy that is efficient and simple to implement in practice.In the paper we present a simulator of the EC2 spot pricing mechanism. The simulator can be easily used to develop and test other bidding strategies on Amazon spot price market.

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“…Such an arrangement, known as over-provisioning [11] [4], brings a number of added issues like excessive power use, dissipation of heat and harmful carbon compounds leading to extensive financial losses for the organization [12]. Also, to manage peak workloads only for short spans yearly, keeping a number of servers functional for the entire year is not at all an efficient option.…”

Section: Dynamic Provisioningmentioning

confidence: 99%

“…Jorge Werner et al [11] introduced a model that ensures the target characteristics of services in Green Computing such as dynamic scalable, Quality-of-Service standard and diminished energy utilization and solves the current problem of over provisioning in data centers w.r.t. the requirement of mapping with the peak load, using CloudSim.…”

Section: Literature Surveymentioning

confidence: 99%

Impact of Energy-Efficient and Eco-Friendly Green Computing

Sharma¹,

Sharma²

2016

IJCA

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With the abrupt advancement in technology, every business organization aspires to migrate to cloud. The technology of cloud computing makes use of the huge data centers that present multiple issues such as extensive amounts of energy consumption, dissipation of lots of heat and methane, carbon dioxide, etc. like deadly green-house compounds and gases. In order to solve all the above stated issues of cloud computing, green computing came out as an improvement over the conventional cloud technology with energy-efficiency, security and environmental-friendliness. The two of the Linear power model and the Low Powerblade model are the existing ones, which employ four Virtual Machine scheduling algorithms for the calculation of consumption of power, are not very eco-friendly and energy efficient. These limitations of the two power models call for the requirement of a better and more efficient power model. Therefore, the research work is motivated to devise such a power model that ensures energy-efficient results and proves it environment-friendly when applied on the data centers in a secure way when compared with the two existing power models on the GreenCloud Simulator.

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Simulator improvements to validate the Green Cloud Computing approach

Cited by 15 publications

References 8 publications

On energy consumption of switch-centric data center networks

On energy consumption of switch-centric data center networks

On optimization of simulation execution on Amazon EC2 spot market

Impact of Energy-Efficient and Eco-Friendly Green Computing

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