Autonomic energy management with Fog Computing
| Autor: | Ricardo do Nascimento Boing, Carlos Becker Westphall, Hugo Vaz Sampaio, Fernando Koch, Rene Nolio Santa Cruz |
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| Rok vydání: | 2021 |
| Předmět: |
General Computer Science
Computer science Energy management 020206 networking & telecommunications 02 engineering and technology Energy consumption Environmental economics Energy management system Variable (computer science) Control and Systems Engineering 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Smart environment Orchestration (computing) Electrical and Electronic Engineering Energy (signal processing) Efficient energy use |
| Zdroj: | Computers & Electrical Engineering. 93:107246 |
| ISSN: | 0045-7906 |
| DOI: | 10.1016/j.compeleceng.2021.107246 |
| Popis: | We introduce an Autonomic System to perform management of energy consumption in Internet of Things (IoT) devices and Fog Computing, including an advanced orchestration mechanisms to manage dynamic duty cycles for extra energy savings. The solution works by adjusting Home (H) and Away (A) cycles based on contextual information, like environmental conditions, user behavior, behavior variation, regulations on energy and network resources utilization, among others. Performance analysis through a proof-of-concept implementation presents average energy savings of up to 61.51% when augmenting with a scheduling system and variable long sleep cycles (LS), and potential for 75.9% savings in specific conditions. We also concluded that there is no linear relation between increasing LS time and additional savings. The significance of this research is to promote autonomic management as a solution to develop more energy efficient buildings and smarter cities, towards sustainable goals. |
| Databáze: | OpenAIRE |
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