DCperf: Data Center Performance

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Past:   Proceedings on DBLP

Future:  Post a CFP for 2017 or later   |   Invite the Organizers Email

 
 

All CFPs on WikiCFP

Event When Where Deadline
DCPerf 2016 International Workshop on Big Data and Cloud Performance
Jun 27, 2016 - Jun 27, 2016 Nara, Japan Feb 17, 2016
DCPerf 2015 Workshop on Data Center Performance
Jun 29, 2015 - Jul 2, 2015 Columbus, Ohio, USA Feb 15, 2015
DCPerf 2014 Workshop on Data Center Performance
Jun 30, 2014 - Jul 3, 2014 Madrid, Spain Feb 7, 2014
DCperf 2013 CFP: ICDCS'13 Workshop on Data Center Performance (DCPerf13) (due on Jan 21th)
Jul 8, 2013 - Jul 11, 2013 Philadelphia, USA Feb 4, 2013
DCPerf 2012 The Second International Workshop on Data Center Perforamnce
Jun 18, 2012 - Jun 21, 2012 Macau, China Jan 30, 2012
DCPerf 2011 The First international Workshop on Data Center Perforamnce
Jun 24, 2011 - Jun 24, 2011 Minneapolis, MN, USA Feb 10, 2011
 
 

Present CFP : 2016

*******************************************************************************

Call for Papers - Submission Due Date: February 17, 2016 (Extended)
The 6th International Workshop on Big Data and Cloud Performance (DCPerf’16)
Naga, Japan, USA, June 27, 2016
http://www.zurich.ibm.com/dcperf16

in conjunction with ICDCS'16:

The 36th IEEE International Conference on Distributed Computing Systems
http://www-higashi.ist.osaka-u.ac.jp/icdcs2016/


Cloud data centers are the backbone infrastructure for tomorrow's information
technology. Their advantages are efficient resource provisioning and low
operational costs for supporting a wide range of computing needs, be it in
business, scientific or mobile/pervasive environments. Because of the rapid
growth in user-defined and user-generated programs, applications and files, the
range of services provided at data centers will expand tremendously and
unpredictably. Particularly, Big Data applications and services present a
unique class of challenges in Cloud. The high volume of mixed workloads and the
diversity of services offered render the performance optimization of data
centers ever more challenging. Moreover, important optimization criteria, such
as scalability, reliability, manageability, power efficiency, area density,
operating cost and many more, often are even mutually exclusive to some extent.
On top of that, the increasing mobility of users across geographically
distributed areas adds another dimension to optimizing big data and cloud
performance
The goal of this workshop is to promote a community-wide discussion to find and
identify suitable strategies to enable effective and scalable performance
optimizations. We are looking for papers that present new techniques, introduce
new theory and methodologies, propose new research directions, or discuss
strategies for resolving open performance problems on Big Data in Clouds.

Topics of Interest
==================

Topics of interest include (but are not limited to):
- Big Data applications and Services
Emerging applications
Programing paradigm
Platforms
Empirical studies
- Data Center systems
Novel architectures
Resource allocation
Content distribution
Evaluation/modeling methodology
- Big Data and Cloud Performance
Cost
Power
Reliability
Performance evaluation/modeling
- Big Data in Cloud
Intra/Inter communication
Network Protocols
Security
Real-time analytics

Important Dates
===============

Paper submission (extended): February 17, 2016
Notification of acceptance: March 4, 2016
Final manuscript due: April 18, 2016

Submission Guideline
====================

Manuscripts must be limited to 6 pages in IEEE 8.5x11 format. Accepted papers
will be published in the combined ICDCS 2016 Workshop proceedings and will be
submitted to IEEE Xplore. Manuscripts should be submitted via
https://easychair.org/conferences/?conf=dcperf16


General Chair
=============

Xiaoyun Zhu, FutureWei Technologies, USA

TPC Chair
=========

Xiaobo Zhou, University of Colorado, USA
Lydia Y. Chen, IBM Zurich Research Lab, Switzerland

Publicity Chair
===============

Robert Birke, IBM Zurich Research Lab, Switzerland

Steering Committee
==================

Jian-Nong Cao, Hong Kong Polytechnic University, Hong Kong
Alok Choudhary, Northwerstern University, USA
Peter Muller, IBM Research Zurich Lab, Switzerland
Martin Schmatz, IBM Research Zurich Lab, Switzerland
Anand Sivasubramaniam, Penn State University, USA
Larry Xue, Arizona State University, USA
 

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