posted by user: yiyuchen || 4798 views || tracked by 9 users: [display]

DCPerf 2011 : The First international Workshop on Data Center Perforamnce

FacebookTwitterLinkedInGoogle


Conference Series : Data Center Performance
 
Link: http://www.zurich.ibm.com/dcperf11/
 
When Jun 24, 2011 - Jun 24, 2011
Where Minneapolis, MN, USA
Submission Deadline Feb 10, 2011
Notification Due Mar 7, 2011
Final Version Due Mar 30, 2011
Categories    performance   data center   cloud computing   archietecture
 

Call For Papers

ANNOUNCEMENT and CALL FOR PAPERS DCPerf 2011

The First International Workshop on Data Center Performance

DCPerf will be held in conjunction with the 31st Int'l Conference on Distributed Computing Systems (ICDCS 2011)
June 24, 2011 Minneapolis, Minnesota, USA

http://www.zurich.ibm/dcperf11

**************************************************************************
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. 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.
We seek submissions of papers that present new techniques, introduce new methodologies, propose new research directions or discuss strategies for resolving open performance problems at all layers of a data center. Focus will be on the data center system level aspects, data center communication, and virtualization & performance optimization.

Topics of interest include (but are not limited to)

– Data Center Communication
Intra/Inter DC communication
Network Protocols
Security
– Data Center Performance
Power
Reliability
– Cloud Computing on Data Center
– Data Center Performance Evaluation
Data mining
Simulation
Modeling
– Data Center System
DC architectures
DC software/applications
Empirical studies
– Data Center Virtualization
Hardware support
Hypervisors
Virtualized storage
Important date
Paper Registration and Submission: Feb 10th, 2011
Notification of Acceptance: Mar 10th 2011
Final Manuscript Due: Mar 30 2011
Submission Guideline

Manuscripts must be limited to 6 pages up to 2 over-length pages in IEEE 8.5x11 format. Accepted papers will be published in the combined ICDCS 2011 workshop proceedings and will be available through IEEE Xplore. Best papers will be solicited for recommended submissions to IEEE Computer Architecture Letters (CAL).


Organizing Committee

General chair
Peter Muller, IBM Zurich Research Lab, Switzerland

Organizer
Lydia Y. Chen, IBM Zurich Research Lab, Switzerland
Xi Zhang, Texas A&M University, USA

Steering Committee
Anand Sivasubramaniam, Penn State University, USA
Jiannong Cao, Hong Kong Polytechnic University, Hong Kong
Guoliang Xue, Arizona State University, USA
Martin Schmatz, IBM Research Zurich Lab, Switzerland
Alok Choudhary, Northwerstern University, USA

Related Resources

ACIIDS 2018   10th Asian Conference on Intelligent Information and Database Systems
BigData Congress 2018   The 7th International Congress on Big Data
DISP 2018   Special Issue on Data Intelligence in Security and Privacy, Journal of Information Security and Applications
IJMPICT 2018   International Journal of Managing Public Sector Information and Communication Technologies
AusDM 2018   Australasian Data Mining Conference
JPS 2018   Journal of Political Science (JPS)
ICMLB 2018   International Conference on Machine Learning and Big Data 2018
IPDCA 2018   7th International conference on Parallel, Distributed Computing and Applications
SI: Cloud-Big Data (SIMPAT) 2018   Special Issue on Modeling and Simulation of Cloud Computing and Big Data, Simulation Modelling Practice and Theory, Elsevier
ICDM 2018   IEEE International Conference on Data Mining