Header menu link for other important links
X
Reduced carbon emission and optimized power consumption technique using container over virtual machine
, V. Vijayakumar
Published in Springer New York LLC
2019
Abstract
Environmental warning is caused by IT industry which critically leads the global pollution with huge amount of toxic carbon emission which is drastically increasing day by day due to demand and usage raised. Due to the environmental warning the industries are in awful need of reducing the carbon foot print by inducing green computing. This paper has achieved green computing by implementing two different algorithms (1) Water Shower Model (WSM) and (2) Trigger—WSM load balancing algorithms, and two different techniques (3) Recommending Containers over virtual machine techniques and 4. DVFS (Dynamic Voltage Frequency Scaling) modeling. The observation between the recommendation systems for container over virtual machine for a sample of four containers with one application each and four virtual machine with one application each is monitored for carbon emission equivalent in kg co 2 for about 1 week is 14 kg co 2 for container and 84.4 kg co 2 for virtual machine, where a drastic difference in the amount of carbon emission is seen. So recommending container will be the best possible solution for the IT based on applications, by enforcing these ideas and techniques the carbon emission can be drastically decreased and the amount of carbon footprint in the atmosphere will also be reduced. The amount of power consumption utilized for the same model is 15.71367 W for container and 94.72667 W for virtual machine is also observed; in the field of IT the power consumption also to be taken into consideration for reducing carbon emission. The recommendation system along with the proposed algorithm will reduce the amount of carbon footprint in the environment. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.
About the journal
JournalData powered by TypesetWireless Networks
PublisherData powered by TypesetSpringer New York LLC
ISSN10220038