Towards energy efficient service composition in green energy powered Cyber–Physical Fog Systems

2020 ◽  
Vol 105 ◽  
pp. 757-765 ◽  
Author(s):  
Deze Zeng ◽  
Lin Gu ◽  
Hong Yao
2021 ◽  
pp. 100101
Author(s):  
Nikolay Aleksandrovich Tsvetkov ◽  
Aleksandr Vital'yevich Tolstykh ◽  
Andrey Nikolaevich Khutornoi ◽  
Stanislav Boldyryev ◽  
Anna Vladimirovna Kolesnikova ◽  
...  

2019 ◽  
Vol 95 ◽  
pp. 89-99 ◽  
Author(s):  
Lin Gu ◽  
Jingjing Cai ◽  
Deze Zeng ◽  
Yu Zhang ◽  
Hai Jin ◽  
...  

2020 ◽  
Vol 391 ◽  
pp. 123551 ◽  
Author(s):  
Qing Chang ◽  
Wenliang Yang ◽  
Fu Li ◽  
Chaorui Xue ◽  
Huiqi Wang ◽  
...  

2020 ◽  
Vol 22 (20) ◽  
pp. 7109-7118
Author(s):  
Iris K. M. Yu ◽  
Jiajun Fan ◽  
Vitaliy L. Budarin ◽  
Florent P. Bouxin ◽  
James H. Clark ◽  
...  

Superheating of starch substrates in microwaves helps to actualize a green, energy-efficient biorefinery of food wastes.


2018 ◽  
Vol 22 (S2) ◽  
pp. 3247-3259 ◽  
Author(s):  
Mohammed Amoon ◽  
Tarek E. El. Tobely

Author(s):  
Achal Kaushik ◽  
Deo Prakash Vidyarthi

The computational grid helps in faster execution of compute intensive jobs. Many characteristic parameters are intended to be optimized while making resource allocation for job execution in computational grid. Most often, the green energy aspect, in which one tries for better energy utilization, is ignored while allocating the grid resources to the jobs. The conventional systems, which propose energy efficient scheduling strategies, ignore other Quality of Service parameters while scheduling the jobs. The proposed work tries to optimize the energy in resource allocation to make it a green energy model. It explores how effectively the jobs submitted to the grid can be executed for optimal energy uses making no compromise on other desired related characteristic parameters. A graph theoretic model has been developed for this purpose. The performance study of the proposed green energy model has been experimentally evaluated by simulation. The result reveals the benefits and gives an insight for an energy efficient resource allocation.


Crystals ◽  
2020 ◽  
Vol 10 (7) ◽  
pp. 589 ◽  
Author(s):  
Yugo Kato ◽  
Michio Suzuki

Metal nanoparticles (NPs), with sizes ranging from 1–100 nm, are of great scientific interest because their functions and features differ greatly from those of bulk metal. Chemical or physical methods are used to synthesize commercial quantities of NPs, and green, energy-efficient approaches generating byproducts of low toxicity are desirable to minimize the environmental impact of the industrial methods. Some microorganisms synthesize metal NPs for detoxification and metabolic reasons at room temperature and pressure in aqueous solution. Metal NPs have been prepared via green methods by incubating microorganisms or cell-free extracts of microorganisms with dissolved metal ions for hours or days. Metal NPs are analyzed using various techniques, such as ultraviolet-visible spectroscopy, electron microscopy, X-ray diffraction, electron diffraction, energy-dispersive X-ray spectroscopy, and X-ray photoelectron spectroscopy. Numerous publications have focused on microorganisms that synthesize various metal NPs. For example, Ag, Au, CdS, CdSe, Cu, CuO, Gd2O3, Fe3O4, PbS, Pd, Sb2O3, TiO2, and ZrO2 NPs have been reported. Herein, we review the synthesis of metal NPs by microorganisms. Although the molecular mechanisms of their synthesis have been investigated to some extent, experimental evidence for the mechanisms is limited. Understanding the mechanisms is crucial for industrial-scale development of microorganism-synthesized metal NPs.


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