MBDS 2012 - International Workshop on Management of Big Data Systems

International Workshop on Management of Big Data Systems (MBDS 2012)
http://www.cercs.gatech.edu/mbds12
In conjunction with ICAC 2012
http://icac2012.cs.fiu.edu
September 21, 2012, San Jose, CA

IMPORTANT DATES
Paper submission due: June 15, 2012
Author notification: July 30, 2012
Workshop: Sep 21, 2012

OVERVIEW
Data is growing at an exponential rate and several systems have emerged
to store and analyze such large amounts of data. These systems, termed
“Big data systems” are fast evolving Examples include the NoSQL storage
systems, Hadoop Map-Reduce, data analytics platforms, search and indexing
platforms, and messaging infrastructures. These systems address needs for
structured and unstructured data across a wide spectrum of domains such
as web, social networks, enterprise, cloud, mobile, sensor networks,
multimedia/streaming, cyberphysical and high performance systems, and
for multiple application verticals such as biosciences, healthcare,
transportation, public sector, energy utilities, oil & gas, and scientific
computing.
With increasing scale and complexity, managing these big data systems to
cope with failures and performance problems is becoming non-trivial.
New resource management and scheduling mechanisms are also needed for such
systems, and so are mechanisms for tuning and support from platform layers.
Several open source and proprietary solutions have been proposed to address
these requirements, with extensive contributions from industry and academia.
However, there remain substantial challenges, including those that pertain
to such systems’ autonomic and self-management capabilities.
The objective of the MBDS workshop is to bring together researchers,
practitioners, system administrators, system programmers, and others
interested in sharing and presenting their perspectives on the effective
management of big data systems. The focus of the workshop is on novel and
practical, systems-oriented work. MBDS offers an opportunity for researchers
and practitioners from industry, academia, and national labs to showcase the
latest advances in this area and to also discuss and identify future directions
and challenges in all aspects on autonomic management of big data systems.
Papers are solicited on all aspects of big data management. Specific topics
of interest include, but are not limited, to the following:
* Autonomic and self-managing techniques
* Application-level resource management and scheduling mechanisms
* System tuning/auto-tuning and configuration management
* Performance management, fault management, and power management
* Scalability challenges
* Complexity challenges, as for composite, cross-tier systems with multiple control loops
* Unified management of ‘data in motion’ and ‘data at rest’
* Dealing with both structured and unstructured data
* Monitoring, diagnosis, and automated behaviour detection
* System-level principles and support for resource management
* Holistic management across hardware and software
* Implications of emerging hardware technologies such as non-volatile memory
* Domain specific challenges in web, cloud, social networks, mobile, sensor networks,
streaming analytics, cyber-physical systems
* System building and experience papers for specific industry verticals

PAPER SUBMISSIONS
Full papers (a maximum of 6 pages in the two-column ACM proceedings
format) are invited on a wide variety of topics relating to management of big
data systems. Submitted papers must be original work, and may not be under
consideration for another conference or journal. Complete formatting and
submission instructions can be found on the workshop web site. Accepted
papers will appear in proceedings distributed at the conference and available
electronically.

WORKSHOP ORGANIZERS
Karsten Schwan, Georgia Tech
Vanish Talwar, HP Labs
PUBLICITY CHAIR
Aravind Menon, Facebook
PROGRAM COMMITTEE
Amitanand Aiyer, Facebook
Adhyas Avasthi, Nokia Research
Milind Bhandarkar, Greenplum Labs, EMC
Randal Burns, John Hopkins University
Garth Gibson, Carnegie Mellon University
Herodotos Herodotou, Duke University
Michael A Kozuch, Intel
Kai Li, Princeton University
Mohamed Mansour, Amazon
Aravind Menon, Facebook
Arif Merchant, Google
Craig Ulmer, Sandia National Lab
Beth Plale, Indiana University
Indrajit Roy, HP Labs
Gabor Szabo, Twitter
Kushagra Vaid, Microsoft
Weikuan Yu, Auburn University
Philip Zeyliger, Cloudera