Analysis of the computational costs of an evolutionary fuzzy rule-based internet-of-things energy management approach

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F25%3A10256407" target="_blank" >RIV/61989100:27240/25:10256407 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S1570870524003263" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1570870524003263</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.adhoc.2024.103715" target="_blank" >10.1016/j.adhoc.2024.103715</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Analysis of the computational costs of an evolutionary fuzzy rule-based internet-of-things energy management approach

Popis výsledku v původním jazyce

This study presents an in-depth analysis of the computational costs associated with the application of an Evolutionary Fuzzy Rule-based (EFR) energy management system for Internet of Things (IoT) devices. In energy-harvesting IoT nodes, energy management is critical for sustaining long-term operation. The proposed EFR approach integrates fuzzy logic and genetic programming to autonomously control energy consumption based on available resources. The study evaluates the system&apos;s computational performance, particularly focusing on processing time, RAM and flash memory usage across various hardware configurations. Different compiler optimization levels and floating-point unit (FPU) settings were also explored, comparing standard and pre-compiled algorithms. The results reveal computational times ranging from 2.43 to 5.23 ms, RAM usage peaking at 6.23 kB, and flash memory consumption between 19 kB and 32 kB. A significant reduction in computational overhead is achieved with optimized compiler settings and hardware FPU, highlighting the feasibility of deploying EFR-based energy management systems in low-power, resource-constrained IoT environments. The findings demonstrate the trade-offs between computational efficiency and energy management, with particular benefits observed in scenarios requiring real-time control in remote and energy-limited environments. © 2024 The Authors

Název v anglickém jazyce

Analysis of the computational costs of an evolutionary fuzzy rule-based internet-of-things energy management approach

Popis výsledku anglicky

This study presents an in-depth analysis of the computational costs associated with the application of an Evolutionary Fuzzy Rule-based (EFR) energy management system for Internet of Things (IoT) devices. In energy-harvesting IoT nodes, energy management is critical for sustaining long-term operation. The proposed EFR approach integrates fuzzy logic and genetic programming to autonomously control energy consumption based on available resources. The study evaluates the system&apos;s computational performance, particularly focusing on processing time, RAM and flash memory usage across various hardware configurations. Different compiler optimization levels and floating-point unit (FPU) settings were also explored, comparing standard and pre-compiled algorithms. The results reveal computational times ranging from 2.43 to 5.23 ms, RAM usage peaking at 6.23 kB, and flash memory consumption between 19 kB and 32 kB. A significant reduction in computational overhead is achieved with optimized compiler settings and hardware FPU, highlighting the feasibility of deploying EFR-based energy management systems in low-power, resource-constrained IoT environments. The findings demonstrate the trade-offs between computational efficiency and energy management, with particular benefits observed in scenarios requiring real-time control in remote and energy-limited environments. © 2024 The Authors

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20201 - Electrical and electronic engineering

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Ad Hoc Networks

ISSN

1570-8705

e-ISSN

1570-8713

Svazek periodika

168

Číslo periodika v rámci svazku

103715

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

9

Strana od-do

nestránkováno

Kód UT WoS článku

001396094700001

EID výsledku v databázi Scopus

2-s2.0-85209989192