@inbook{550efec6e02548438da7a60b2d397639,
title = "Optimizing the use of renewable energy to minimize operational costs in distributer green data centers",
abstract = "Green data centers are more and more deployed worldwide. They integrate many renewable sources to provide clean power and decrease their operating cost. GDCs are typically deployed over multiple locations where renewable energy availability, bandwidth prices, and grid electricity cost have high geographical diversity. This chapter focuses on delay-bounded applications in distributed GDCs (DGDCs) and performs cost and energy-effective scheduling of multiple heterogeneous applications verifying delay-bound constraints of different tasks. DGDCs' operational cost minimization problem is formulated and successfully optimized using multiple optimization approaches. Real-life data trace-driven experiments are conducted to assess and compare the effectiveness of the different approaches at solving this problem. High-performance task scheduling results are obtained. The operational cost of each GDC is minimized, and the utilization of solar and wind renewable energy from the different geographical locations is maximized while delay-bound constraints of all tasks are strictly met.",
keywords = "Bat algorithm, Cloud computing, Cost optimization, Firefly algorithm, Simulated annealing, Task scheduling",
author = "{Chiheb Ammari}, Ahmed",
note = "Publisher Copyright: {\textcopyright} 2023 Elsevier Inc. All rights reserved.",
year = "2023",
month = jan,
day = "1",
doi = "10.1016/b978-0-443-18439-0.00008-2",
language = "English",
isbn = "9780443184390",
volume = "2",
series = "Renewable Energy Production and Distribution: Solutions and Opportunities: Volume 2",
publisher = "Academic Press",
pages = "461--489",
booktitle = "Renewable Energy Production and Distribution: Solutions and Opportunities: Volume 2",
address = "United Kingdom",
}