Engineering and Management of Data Centers: An IT Service Management Approach

290 Pages·2017·9.19 MB·English

by  Jorge Marx Gómez et al. (eds.)

Service Science: Research and Innovations in the Service Economy
Jorge Marx Gómez
Manuel Mora
Mahesh S. Raisinghani
Wolfgang Nebel
Rory V. O’Connor Editors
Engineering
and
Management
of Data Centers
An IT Service Management Approach
Service Science: Research and Innovations
in the Service Economy
Series Editors
Bill Hefley
Wendy Murphy
More information about this series at http://www.springer.com/series/8080
Jorge Marx Gómez • Manuel Mora
Mahesh S. Raisinghani • Wolfgang Nebel
Rory V. O’Connor
Editors
Engineering
and Management
of Data Centers
An IT Service Management Approach
Editors
Jorge Marx Gómez Manuel Mora
Department of Computing Sciences Department of Information Systems
Carl von Ossietzky University Oldenburg Autonomous University of Aguascalientes
Oldenburg, Germany Aguascalientes, Mexico
Mahesh S. Raisinghani Wolfgang Nebel
College of Business Department for Computing Science
Texas Woman’s University Denton Carl von Ossietzky University of Oldenburg
Dallas, Houston Oldenburg, Germany
TX, USA
Rory V. O’Connor
School of Computing
Dublin City University
Dublin, Ireland
ISSN 1865-4924 ISSN 1865-4932 (electronic)
Service Science: Research and Innovations in the Service Economy
ISBN 978-3-319-65081-4 ISBN 978-3-319-65082-1 (eBook)
DOI 10.1007/978-3-319-65082-1
Library of Congress Control Number: 2017956900
© Springer International Publishing AG 2017
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Contents
Foundations of Data Center: Key Concepts and Taxonomies . . . . . . . . . . 1
Cathleen Carey, Mahesh S. Raisinghani, and Becky White
ITSDM: A Methodology for IT Services Design . . . . . . . . . . . . . . . . . . . . . 15
Manuel Mora, Jorge Marx Gómez, Rory V. O’Connor,
and Burkard Meyendriesch
Using Dashboards to Reach Acceptable Risk in Statistics
Data Centers Through Risk Assessment and Impact . . . . . . . . . . . . . . . . . 41
Atif Amin and Raul Valverde
Risk and Data Center Planning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
Kurt J. Engemann and Holmes E. Miller
Best Practices in Data Center Management:
Case – KIO Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91
Teresa Lucio-Nieto and Dora Luz González-Bañales
QoS in NaaS (Network-as-a-Service) Using Software
Defined Networking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115
Ammar AlSous and Jorge Marx Gómez
Optimization of Data Center Fault Tolerance Design . . . . . . . . . . . . . . . . . 141
Sascha Bosse and Klaus Turowski
Energetic Data Center Design Considering Energy
Efficiency Improvements During Operation . . . . . . . . . . . . . . . . . . . . . . . . 163
Stefan Janacek and Wolfgang Nebel
Demand-Side Flexibility and Supply-Side Management:
The Use Case of Data Centers and Energy Utilities . . . . . . . . . . . . . . . . . . 187
Robert Basmadjian, Florian Niedermeier, and Hermann de Meer
DevOps: Foundations and Its Utilization in Data Center . . . . . . . . . . . . . . 205
Mirna Muñoz and Oswaldo Díaz
v
vi Contents
Sustainable and Resilient Network Infrastructure Design
for Cloud Data Centers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227
Ritchie Qi, William Liu, Jairo Gutierrez, and Mamta Narang
Application Software in Cloud-Ready Data Centers: A Survey . . . . . . . . . 261
Johannes Hintsch, Ateeq Khan, André Siegling, and Klaus Turowski
Contributors
Ammar AlSous Department of Business Information Systems/Very Large
Business Applications (VLBA), Carl von Ossietzky University of Oldenburg,
Oldenburg, Germany
Atif Amin Dubai Statistics Center, Dubai, United Arab Emirates
Robert Basmadjian Department of Computer Science and Mathematics,
University of Passau, Passau, Germany
Sascha Bosse Magdeburg Research and Competence Cluster for Very Large
Business Applications, Faculty of Computer Science, Otto-von-Guericke University
Magdeburg, Magdeburg, Germany
Cathleen Carey Executive MBA Program, School of Management, Texas
Woman’s University, Denton, TX, USA
Oswaldo Díaz Group of Systems Engineering, National Institute of Statistics and
Geography, Mexico
Kurt J. Engemann Center for Business Continuity and Risk Management, Iona
College, New Rochelle, NY, USA
Dora Luz González-Bañales Department of Systems and Computing, Instituto
Tecnológico de Durango, Durango, Mexico
Jairo Gutierrez Department of Information Technology and Software Engineering,
School of Engineering, Computer and Mathematical Sciences, Auckland University
of Technology, Auckland, New Zealand
Johannes Hintsch Magdeburg Research and Competence Cluster for Very Large
Business Applications, Faculty of Computer Science, Otto-von-Guericke University
Magdeburg, Magdeburg, Germany
Stefan Janacek Smart Resource Integration, OFFIS Institute for Information
Technology, Lower Saxony, Germany
vii
viii Contributors
Ateeq Khan Magdeburg Research and Competence Cluster for Very Large
Business Applications, Faculty of Computer Science, Otto-von-Guericke University
Magdeburg, Magdeburg, Germany
William Liu Department of Information Technology and Software Engineering,
School of Engineering, Computer and Mathematical Sciences, Auckland University
of Technology, Auckland, New Zealand
Teresa Lucio-Nieto Universidad Iberoamericana, ITESM & Universidad Anahuac,
Customer Care Associates, Monterrey, Nuevo León, Mexico
Jorge Marx Gómez Department of Computing Sciences, Carl von Ossietzky
University Oldenburg, Oldenburg, Germany
Hermann de Meer Department of Computer Science and Mathematics, University
of Passau, Passau, Germany
Burkard Meyendriesch IT Services Department, Carl von Ossietzky University
Oldenburg, Oldenburg, Germany
Holmes E. Miller Department of Accounting, Business, Economics and Finance,
Muhlenberg College, Allentown, PA, USA
Manuel Mora Department of Information Systems, Autonomous University of
Aguascalientes, Aguascalientes, Mexico
Mirna Muñoz Mathematic Research Center, Zacatecas, Mexico
Mamta Narang Department of Information Technology and Software Engineering,
School of Engineering, Computer and Mathematical Sciences, Auckland University
of Technology, Auckland, New Zealand
Wolfgang Nebel Department of Informatics, Carl von Ossietzky University
Oldenburg, Lower Saxony, Germany
Florian Niedermeier Department of Computer Science and Mathematics,
University of Passau, Passau, Germany
Rory V. O’Connor School of Computing, Dublin City University, Glasnevin,
Dublin, Ireland
Ritchie Qi Department of Information Technology and Software Engineering,
School of Engineering, Computer and Mathematical Sciences, Auckland University
of Technology, Auckland, New Zealand
Mahesh S. Raisinghani College of Business, Texas Woman’s University Denton,
Dallas, Houston, TX, USA
André Siegling Magdeburg Research and Competence Cluster for Very Large
Business Applications, Faculty of Computer Science, Otto-von-Guericke University
Magdeburg, Magdeburg, Germany
Contributors ix
Klaus Turowski Magdeburg Research and Competence Cluster for Very Large
Business Applications, Faculty of Computer Science, Otto-von-Guericke University
Magdeburg, Magdeburg, Germany
Klaus Turowski Magdeburg Research and Competence Cluster for Very Large
Business Applications, Faculty of Computer Science, Otto-von-Guericke University
Magdeburg, Magdeburg, Germany
Raul Valverde Department of Supply Chain and Business Technology
Management, Concordia University, Montreal, QC, Mexico
CONAIC, Mexico City, Mexico
Becky White Executive MBA Program, School of Management, Texas Woman’s
University, Denton, TX, USA
Foundations of Data Center: Key Concepts
and Taxonomies
Cathleen Carey, Mahesh S. Raisinghani, and Becky White
Abstract Many corporations use central data centers to avoid building and main-
taining a separate data center and are finding and adopting new ways to make the
data centers more energy efficient. This chapter provides a relevant summary of key
concepts for understanding the complexity of data centers and the types and value
of data centers. Its purpose is to provide information and understanding needed to
manage massive data generated every day in the era of internet technology.
1 Introduction
This chapter provides a relevant summary of key concepts for understanding the com-
plexity of data centers. Its purpose is to provide information and understanding needed
to manage massive data generated every day in the era of internet technology. From
huge corporate businesses, share markets to even social media, the amount of data
generated has increased manifold. While internet has been a boon to the world with
the connectivity and the speed it offers, it is only with the help of data centers that
numerous thousands of gigabytes are still generated and stored and still retrieved
quickly from anywhere. Data centers are essential and what’s even more necessary is
to have data centers that are environmentally friendly and economic to maintain. With
the growth of business being conducted online, more business systems are classified
as mission-critical. Typically, 58% of the business systems of an organization are clas-
sified as mission-critical, and these require additional investments in data center facili-
ties, IT technology, business processes, and IT staff (Cocchiara et al. 2008).
The chapter is organized as follows. The chapter starts with fundamental con-
cepts and then an overview of data centers. Next it describes the evolution of data
C. Carey • B. White
Executive MBA Program, School of Management, Texas Woman’s University,
Denton, TX 76204, USA
e-mail: [e-mail]; [e-mail]
M.S. Raisinghani (*)
College of Business, Texas Woman’s University Denton, Dallas, Houston, TX, USA
e-mail: [e-mail]
© Springer International Publishing AG 2017 1
J. Marx Gómez et al. (eds.), Engineering and Management of Data Centers,
Service Science: Research and Innovations in the Service Economy,
DOI 10.1007/978-3-319-65082-1_1