Thanks to the many ISSIP ambassadors who participated in person at Prof David Lee’s talk…
CFP: Engineering and Management of Data Centers: an IT Service Management Approach
******* Call for Chapters *******
Book titled:
“Engineering and Management of Data Centers: an IT Service Management Approach”
Book series:
“Service Science: Research and Innovations in the Service Economy”
Springer-Verlag, London Ltd.
BOOK’S OBJECTIVE:
This book will cover essential, modern and emergent knowledge on the
engineering and management of data centers. Data centers are currently key
organizational assets, and their high value proposition in ensuring
business continuity operations has been highlighted. Topics include
planning, design, implementation, operation and control, maintenance,
reallocation and disposal of data centers from a research, didactical and
practitioner viewpoint. Expected readers are practitioners in data
centers, researchers in the area and faculty teaching related courses on
data centers.
BOOK’S RATIONALE:
Data centers are installations specifically built with the primary purpose
to house, and provide the adequate environmental conditions (space, power,
cooling, and physical security) for the computer and telecommunication
equipment used in an organization (Snevely, 2002). Data centers have been
a relevant organizational asset for containing valuable information
resources and channels for providing IT functionalities to local and
remote end users. Furthermore, in the last decade, with the explosion of
web-based and inter-organizational systems for local and remote, and
internal and external users, in large and medium-sized organizations with
international operations, the data centers can be considered as
mission-critical assets whose availability, performance, power efficiency,
security, continuity, and overall effectiveness must be guaranteed in
order to avoid critical downtimes (Arregoces and Portolani, 2003; Bilal et
al., 2013). Industry reports (Siemon, 2005; ENP, 2011) indicate that 1-hr
downtime costs in data centers varies from US $10,000 to US $6,000,000 to
organizations providing services such as: ATM, cellular services, air line
reservations, on-line shopping, package shipping, credit card
authorizations, and brokerage operations. Additional to direct financial
costs, organizations can also suffer negative impacts from a data center’s
downtime on: image by business disruption, end-user productivity, IT
productivity, and third-party operational delay (ENP, 2011).
The planning, design, implementation, operation and control, maintenance,
evolution, and disposal (when the useful data center’s life has been
reached) of data centers, in modern times represents a complex process
(Holtsnider and Jaffe, 2012). The explosion of Information and
Communication Technologies (ICT) has introduced engineering technical
challenges for data centers engineers. Consequently, data center planning
and design processes must consider relevant issues such as: integration,
interoperability, security, reliability, serviceability, manageability,
controllability, scalability, safety, virtualization, energy efficiency
and overall performance by including a myriad of ICT (Greenberg et al.,
2006; Daim et al., 2009; Alaraifi et al., 2013; Covas et al., 2013). In
turn, the economic, and socio-political environmental international issues
have also introduced managerial challenges for data center managers
regarding green IT initiatives, IT service management initiatives, IT
managerial cost reduction, provision of effective valued IT services,
timely release of IT services, and assuring a high IT service availability
and continuity status (Conger et al., 2008; Galup et al., 2009). In
particular, the conceptualization of data centers as service systems (Mora
et al., 2009; Törhönen, 2014) and the link with the design of IT services
(Mora et al., 2015) as well as their final implementation in data centers
is missing in the literature.
Hence, updated, integrative, scientific and practical knowledge is
required to address this engineering and managerial complexity for
planning, designing, implementing, operating and controlling, maintaining,
evolving, and disposal of data centers. Traditionally, the knowledge
sources on data center processes have come from the ICT industry.
Nevertheless, we consider that knowledge with rigor and relevance must be
produced from both academia and industry. ICT academia has published
research on IT service management process frameworks, cloud computing
performance models (Bilal et al., 2014), and other related issues. On the
other hand, ICT industry has advanced with green IT metrics (Daim et al.,
2009; Loos et al., 2011; Wang and Khan, 2011), maturity models (Singh et
al., 2011) and best practices for software development such as DevOps (Kim
et al., 2015; Stier et al., 2015) where data center engineers are included
for a fast and correct software release (Pollard et al., 2010; Kliazovich
et al., 2012).
Furthermore, we consider that the knowledge gap between the academic and
industry perspectives has widened regarding the engineering and management
of data centers. This is due to the explosion of ICT, the high costs for
having data centers laboratories in the academic environment, the lack of
textbooks on Data Centers, and the scarcity of undergraduate and graduate
courses on these topics (Schaeffer, 1981; Gusev et al., 2014; Memari et
al., 2014).
REFERENCES upon request.
KEY TOPICS:
High quality fundamental, applied research-oriented and didactical
practitioner-viewpoints chapters are welcome on the following key topics
that include (but are not limited to):
Section I. Foundations on data centers
• Fundamental concepts
• Overview of data centers
• Evolution of data centers
• Types of data centers (business vs scientific; centralized vs distributed, tiers I, II, III or IV; private vs cloud vs ISP)
• Organizational charts for data centers
• Taxonomies of services provided and consumed in data centers
• The data center as a service system
• Value of data centers
Section II. Data centers engineering
• General and integrative design methodologies for data centers
• Specific design methods for data center dimensions (e.g. for space layout, for power design, for cooling design, etc)
• Design tools applied to data centers
• Design simulation tools applied to data centers
• Data center architecture design
• Data center design and ICT architecture design
• Data center
• Data centers and virtualization approaches
• Data centers and ITSM tools (commercial ones)
• Data centers and ITSM tools (open source ones)cases of
• Data centers equipment benchmarks
• Data centers software systems benchmarks
• Data centers performance simulation methods
• Data centers reliability simulation methods
Section III. Data centers management
• Data centers selection methods
• Data centers planning methods
• Data centers risk management methods
• Data centers implementation methods
• Data centers operation and control methods
• Data centers security methods and approaches
• Data centers disaster recovery planning methods
• Data centers capacity planning methods
• Data centers performance evaluation methods
• Data centers retirement or re-allocation methods
• Data centers maturity models
• Data centers metrics (PUE, DCiE, DCP, DCeP, among others)
• Data centers servers metrics ( SPECvirt_sc2013, SPEC CPU2006, SPECweb2009, SPECmail2009, etc)
• Data centers dashboards and others DMSS
• Data centers and automation services
• Data centers backup methods and approaches
• Data centers standards (TIA 942, Uptime Institute Framework, IEEE 493, etc)
• Data centers certifications
• Data center education in undergraduate and graduate programs
• Data centers financial methods
• Data centers equipment selection and evaluation methods
• Human resource management in data centers
• Data centers end-user satisfaction and quality of service surveys
• Data centers and ITSM frameworks (ITIL, CobIT, CMMI-SVC, MOF 4, ITUP, ISO 20K)
Section IV. Data centers emergent topics, challenges and trends
• Green data centers design approaches
• DevOps methods
• Cloud computing architectures for data centers
• Centralized vs distributed data centers
• Software-defined data center (SDDC)
• Economic value of data centers
• Economic models for allocation of data centers
• Data centers for small organizations
• Corporative data centers challenges and trends
• Analytics for data centers
• Data centers trends
• Data centers challenges
IMPORTANT DATES:
May 31, 2016 – full chapter submission deadline.
July 15, 2016 – editorial decision deadline (accepted, conditioned or
rejected chapter).
August 15, 2016 – conditioned chapter submission deadlines.
September 15, 2016 – editorial decision deadline on conditioned chapters.
September 31, 2016 – camera-ready chapter submission deadline.
First 2017 quarter – estimated publishing period.
SUBMISSION PROCESS:
Interested authors, please send your full chapter before or on May 31,
2016 to Manuel Mora at mmora@securenym.net with copy to
jorge.marx.gomez@uni-oldenburg.de. Each chapter will be evaluated by at
least two academic and professional peers on related themes in a blind
mode for assessing an editorial decision among: accepted, conditioned or
rejected chapter. Conditioned chapters will have an additional opportunity
for being improved and evaluated. In the second round evaluation for the
conditioned chapters, a definitive editorial decision among: accepted or
rejected will be reported. All of the accepted chapters must be submitted
according to the Editorial publishing format rules timely. Instructions
for authors can be downloaded at the following web links:
http://www.springer.com/cda/content/document/cda_downloaddocument/T1-book.zip?SGWID=0-0-45-392600-0
CO-EDITORS:
Jorge Marx Gómez, Carl von Ossietzky Universität Oldenburg, Germany
Manuel Mora, Autonomous University of Aguascalientes, Mexico
Rory O’Connor, Dublin City University, Ireland
Wolfgang Nebel, Carl von Ossietzky Universität Oldenburg, Germany
Mahesh Raisinghani, Texas Woman’s University, USA