TY - GEN
T1 - Automated Energy Modeling Framework for Microcontroller-Based Edge Computing Nodes
AU - Lange, Emanuel Oscar
AU - Jose, Jiby Mariya
AU - Benedict, Shajulin
AU - Gerndt, Michael
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2023
Y1 - 2023
N2 - When IoT-enabled applications utilized edge nodes rather than cloud servers, they aimed to apply diligent energy-efficient mechanisms on edge devices. Accordingly, frameworks and approaches that monitor/model microcontrollers, including Espressif-Processor-based (ESP) edge nodes, have drawn mainstream attention among researchers working in the edge intelligence domain. The traditional approaches to measuring the energy consumption of edge nodes are either not online or prone to complex solutions. This article attempts to develop an Automated Energy Modeling Framework (AEM) for microcontroller-based edge nodes of IoT-enabled applications. The proposed approach baselines the energy consumption values; models energy consumption values of components using a random forest (RF) algorithm; and, automatically suggests the energy consumption of edge nodes in real-time – i.e., during the execution of IoT-enabled applications on edge nodes. Experiments were carried out to validate two applications’ automated energy modeling approach using Espressif’s ESP devices. The proposed mechanism would benefit energy-conscious IoT-enabled application developers who focus on minimizing the energy consumption of embedded-based edge nodes such as ESPs.
AB - When IoT-enabled applications utilized edge nodes rather than cloud servers, they aimed to apply diligent energy-efficient mechanisms on edge devices. Accordingly, frameworks and approaches that monitor/model microcontrollers, including Espressif-Processor-based (ESP) edge nodes, have drawn mainstream attention among researchers working in the edge intelligence domain. The traditional approaches to measuring the energy consumption of edge nodes are either not online or prone to complex solutions. This article attempts to develop an Automated Energy Modeling Framework (AEM) for microcontroller-based edge nodes of IoT-enabled applications. The proposed approach baselines the energy consumption values; models energy consumption values of components using a random forest (RF) algorithm; and, automatically suggests the energy consumption of edge nodes in real-time – i.e., during the execution of IoT-enabled applications on edge nodes. Experiments were carried out to validate two applications’ automated energy modeling approach using Espressif’s ESP devices. The proposed mechanism would benefit energy-conscious IoT-enabled application developers who focus on minimizing the energy consumption of embedded-based edge nodes such as ESPs.
KW - Automation
KW - Energy consumption
KW - Energy modeling
KW - Framework
KW - IoT
UR - http://www.scopus.com/inward/record.url?scp=85151147979&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-28180-8_29
DO - 10.1007/978-3-031-28180-8_29
M3 - Conference contribution
AN - SCOPUS:85151147979
SN - 9783031281792
T3 - Communications in Computer and Information Science
SP - 422
EP - 437
BT - Advanced Network Technologies and Intelligent Computing - 2nd International Conference, ANTIC 2022, Proceedings
A2 - Woungang, Isaac
A2 - Dhurandher, Sanjay Kumar
A2 - Pattanaik, Kiran Kumar
A2 - Verma, Anshul
A2 - Verma, Pradeepika
PB - Springer Science and Business Media Deutschland GmbH
T2 - 2nd International Conference on Advanced Network Technologies and Intelligent Computing, ANTIC 2022
Y2 - 22 December 2022 through 24 December 2022
ER -