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The Methods and Approaches of Explainable Artificial Intelligence Read chapter Read first chapter

2021 | OriginalPaper | Chapter

Renewable Energy-Aware Heuristic Algorithms for Edge Server Selection for Stream Data Processing

Authors : Tomasz Szydlo, Chris Gniady

Published in: Computational Science – ICCS 2021

Publisher: Springer International Publishing

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Abstract

Internet of Things and Edge computing are evolving, bringing data processing closer to the source and a result closer to the network’s edge. This distributed processing can increase energy consumption and carbon footprint. One solution to overcome the environment’s impact is using renewable energy sources such as photovoltaic panels to power both cloud and edge servers. Since solar energy is not available at night or can vary with cloudiness, the centers still rely on conventional energy sources. Any solar energy that exceeds the demand power of the computing infrastructure is put back to the grid. Fluctuations in energy output due to moving clouds can have a negative impact on conventional energy suppliers as they have to maintain a constant energy supply. This paper presents heuristic algorithms for selecting edge servers for data stream processing to manage renewable energy utilization and smooth out energy fluctuations.

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Metadata
Title
Renewable Energy-Aware Heuristic Algorithms for Edge Server Selection for Stream Data Processing
Authors
Tomasz Szydlo
Chris Gniady
Copyright Year
2021
Book
Computational Science – ICCS 2021

Print ISBN: 978-3-030-77969-6

Electronic ISBN: 978-3-030-77970-2

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-3-030-77970-2_49

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