Nimrod Megiddo
Journal of Symbolic Computation
Cloud computing revolutionised the development and execution of distributed applications by providing on-demand access to virtual resources. Containerisation simplifies management and support of the cloud infrastructure and applications. Clouds typically are consumed in a pay-as-you-go pricing model. However, when applied to containerised environments, such traditional models do not consider resource utilisation values, leading to inaccurate estimates. Moreover, these models do not consider energy consumption, a dominant component of the data centre’s total cost of ownership. This paper proposes Energy Price Cloud Containers (EPCC), a cost model based on energy consumption that accounts for containers’ effective resource utilisation. We compare EPCC with AWS Fargate to highlight the benefits of using an energy-based pricing model. Thus, by comparing the cost of an application running using AWS Fargate with the estimated cost of that application in nome, it is possible to identify the benefits of using an energy-based pricing model. The weekly costs estimated when running computational resources at nome vary between US 10.59. In contrast, when estimating the same amount of resources on AWS Fargate, the costs vary between US 29.94. Nome resulted in a cost reduction of up to 35%.
Nimrod Megiddo
Journal of Symbolic Computation
David W. Jacobs, Daphna Weinshall, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence
J. LaRue, C. Ting
Proceedings of SPIE 1989
Arnon Amir, Michael Lindenbaum
IEEE Transactions on Pattern Analysis and Machine Intelligence