MBDS 2012 - International Workshop on Management of Big Data Systems

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Category MBDS 2012

Deadline: June 15, 2012 | Date: September 21, 2012

Venue/Country: San Jose, U.S.A

Updated: 2012-04-30 22:13:11 (GMT+9)

Call For Papers - CFP

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