Performance comparison of ESP-r in containers vs virtual machines for digital twins

Conference paper

Jawara, F., Seeam, A. and Ramsurrun, V. 2024. Performance comparison of ESP-r in containers vs virtual machines for digital twins. 2024 International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems. Port Louis, Mauritius 01 - 02 Aug 2024 IEEE. https://doi.org/10.1109/icabcd62167.2024.10645255
TypeConference paper
TitlePerformance comparison of ESP-r in containers vs virtual machines for digital twins
AuthorsJawara, F., Seeam, A. and Ramsurrun, V.
Abstract

This study compares the performance of the ESP-r building energy modeling tool in containerized environments (Docker, LXD, LXC) versus traditional virtual machines (VMs, VirtualBox, VMware), focusing on execution time, resource utilization, and scalability. Given the increasing adoption of cloud computing and virtualization, it's crucial to identify the most efficient platform for ESP-r simulations. The hypothesis suggests that containers, due to their lightweight architecture, may offer superior performance compared to VMs. The research involves setting up ESP-r in both environments, conducting simulations, and recording execution times to determine the optimal virtualization technology. Additionally, the study examines the role of these technologies in supporting digital twins, dynamic virtual representations of physical systems used for performance monitoring and decision-making in the construction industry.

Sustainable Development Goals11 Sustainable cities and communities
9 Industry, innovation and infrastructure
13 Climate action
Middlesex University ThemeCreativity, Culture & Enterprise
Conference2024 International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems
Proceedings Title2024 International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems (icABCD)
ISBN
Electronic9798350387902
Hardcover9798350387919
PublisherIEEE
Publication dates
Online29 Aug 2024
Print01 Aug 2024
Publication process dates
Accepted2024
Deposited30 Sep 2026
Output statusPublished
Digital Object Identifier (DOI)https://doi.org/10.1109/icabcd62167.2024.10645255
Web address (URL) of conference proceedingshttp://doi.org/10.1109/icABCD62167.2024
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