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BINARY PROGRAMMING MODELS FOR THE SERVER CONSOLIDATION PROBLEM IN DATA CENTERS

Delia Radulescu

First published: 2018-06-20https://doi.org/10.5593/sgem2018/2.1/s07.026View metrics

Abstract

The last decade has witnessed an exponential increasing in the number and the size of data centers. This expansion was driven by the increasing demand for digital products and services from the various sectors of the economy. Data center operators are faced with an increasing pressure for managing their facilities more efficiently and cost effectively such that they achieve 100 percent uptime. This is a difficult task to overcome, taking into account that energy consumption is the fastest growing component of data center. In an effort to answer this challenge, data center operators are using a virtualization technology. It enables each user to work with his own virtual machine that has its own operating system. Instead that the users have several independent computers, they run at the same time on the same server. Server consolidation is a technology that simplifies the administration of a data center. It improves energy efficiency by improving resource utilizations and reducing the number of active servers (physical machines) in the contemporary service-oriented data centers. We formulate several binary programming models for the static server consolidation problem that determine the best placement of virtual machines on servers (physical machines) in a data center. One model minimizes the energy consumption of the data center. In case that the servers are of the same type this is equivalent with the minimization of the number of active servers. Another model maximizes the use of server resources (CPU, memory, bandwidth etc). Decision variables are represented by a binary vector that shows which servers are active and by a binary matrix that shows the allocation of virtual machines to servers.

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Publication details

Title
BINARY PROGRAMMING MODELS FOR THE SERVER CONSOLIDATION PROBLEM IN DATA CENTERS
Authors
Delia Radulescu
Proceedings
SGEM International Multidisciplinary Scientific GeoConference EXPO Proceedings; 18th International Multidisciplinary Scientific GeoConference SGEM2018, Informatics, Geoinformatics and Remote Sensing
Publisher
STEF92 Technology
Year
2018
Pages
201-208
SWS Citekey
Radulescu20187201208
ISSN
1314-2704
ISBN
978-619-7408-39-3
Language
en
Publication type
Conference Paper
Keywords
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