Green Cloud Meta-Scheduling

Carvalho, Osvaldo Adilson de; Bruschi, Sarita Mazzini; Santana, Regina Helena Carlucci; Santana, Marcos José

doi:10.1007/s10723-015-9333-z

Cited by 11 publications

(4 citation statements)

References 20 publications

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“…It is possible to extend this solution to the green IT platform. A variation of GreenMACC was proposed and evaluated by de Carvalho Junior et al (2016). In their pioneering work, Fioccola et al (2016) proposed a new energyaware resource arrangement framework for distributed cloud infrastructures.…”

Section: Architecture-based Approachmentioning

confidence: 99%

Green Computing – A Survey of the Current Technologies

Bose

Nag

2022

APJMT

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Cloud computing is a dynamic technology with various application spheres because of its scalability, cost-effectiveness, and reliability. However, since the energy demand for information and Communication Technologies (ICT) is on the rise, cloud computing is facing new challenges related to environmental protection, power consumption, energy efficiency, and carbon dioxide emissions. The latest technologies that strive for sustainable energy efficiency and a reduced e-waste and carbon footprint are constantly being researched and deployed. These technologies have the potential to transform cloud computing into green cloud computing. In this survey, the authors investigated recent research methodologies such as algorithm-based, architecture-based, framework-based, model-based, methods-based, and general issue-based approaches. Many of these research projects are still in their infancy and are yet to be commercially implemented. The last thing that was talked about was some future research trends and some of the open challenges in green cloud computing.

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Section: Architecture-based Approachmentioning

confidence: 99%

Green Computing – A Survey of the Current Technologies

Bose

Nag

2022

APJMT

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“…The jobs could e.g. have priorities and deadlines, and the system would then assign them appropriately for computing [8]. Also existing studies on scheduling in volunteer computing could be adapted for optimizing the scheduling [5,52].…”

Section: Control and Sensory Systemsmentioning

confidence: 99%

Sunburn—using excess energy of small-scale production for distributed computing

Nurminen

Niemi²,

Strandman

et al. 2017

Energy Efficiency

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The Sunburn solar computer system is based on the idea of consuming the excess electricity of photovoltaic energy systems for useful computing. In this way, the proposed approach allows us to move a part of computing capacity from dedicated data centers to individual solar energy systems and thereby reduce the energy consumption of the data centers. In principle, the proposed mechanism converts the excess electrical energy into valuable computation. The results of computation or data processing are easier to store and transfer than produced electricity. In small scale systems, the benefit from storing or selling the excess electricity is small, whereas the benefit from selling the generated data is potentially larger, as we demonstrate in this study. Finally, the technical feasibility of the solution is illustrated by constructing and evaluating a prototype implementation using excess solar energy for distributed BOINC computing. Keywords distributed computing • solar energy • green computing • energy storage • scientific computing • distributed data center Address(es) of author(s) should be given

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“…The resource economy is considered as the main factor in this area. 19,20 The software level energy optimizations are effective in reducing energy consumption and its demand. Today, there is more emphasis on the software level energy optimizations with resource management systems, virtual machine (VM) migration techniques, scheduling algorithms, resource allocation strategies, and so forth.…”

Section: Introductionmentioning

confidence: 99%

A new metaheuristic‐based method for solving the virtual machines migration problem in the green cloud computing

Abnoosian

2021

Concurrency and Computation

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Cloud computing (CC) provides dynamic hiring of server abilities as scalable virtualized services to end-users. However, data center hosting wastes massive amounts of energy resulting in high operational costs and carbon footprints. Also, virtualization is one of CC's main features, and physical resources are delivered by virtual machine (VM).Therefore, in the present article, a new method is provided to improve the VM energy consumption and execution time in the VM migration problem using a hybrid optimization algorithm. Since this issue is one of the famous NP-hard problems, a method is proposed in this article works based on genetic algorithm (GA) and particle swarm optimization (PSO) algorithm. The hybrid algorithm uses a GA to dominate PSO algorithms' constraints, such as weak convergence and stymie in global optima. The CloudSim simulator is employed to show the efficiency of the method compared to others. Using this method will keep the proficiency and power performance of the data centers at the same level. The results showed that energy consumption in the proposed method is better than the other three methods and has been improved by an average of 23.19%. Also, the results showed that execution time is better than the other three methods and has been improved by an average of 29.01%.

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Green Cloud Meta-Scheduling

Cited by 11 publications

References 20 publications

Green Computing – A Survey of the Current Technologies

Green Computing – A Survey of the Current Technologies

Sunburn—using excess energy of small-scale production for distributed computing

A new metaheuristic‐based method for solving the virtual machines migration problem in the green cloud computing

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