Publication: Cutting down the energy cost of geographically distributed cloud data centers
Program
KU-Authors
KU Authors
Co-Authors
Cambazoğlu, Berkant Barla
Publication Date
Language
Embargo Status
Journal Title
Journal ISSN
Volume Title
Alternative Title
Abstract
The energy costs constitute a significant portion of the total cost of cloud providers. The major cloud data centers are often geographically distributed, and this brings an opportunity to minimize their energy cost. In this work, we model a geographically distributed data center network that is specialized to run batch jobs. Taking into account the spatio-temporal variation in the electricity prices and the outside weather temperature, we model the problem of minimizing the energy cost as a linear programming problem. We propose various heuristic solutions for the problem. Our simulations using real-life workload traces and electricity prices demonstrate that the proposed heuristics can considerably decrease the total energy cost of geographically distributed cloud data centers, compared to a baseline technique.
Source
Publisher
Springer-Verlag Berlin
Subject
Computer science, Information systems, Theory methods
Citation
Has Part
Source
Energy Efficiency in Large Scale Distributed Systems, EE-LSDS 2013
Book Series Title
Edition
DOI
10.1007/978-3-642-40517-4_23