1. Description
Technology advances in communications, computation, and storage result in huge collections of data, capturing information of value to business, science, government, and society. Data volumes are currently growing faster than Moore’s law. Looking forward, the exponential growth is not likely to stop. The huge size of data is imposing big challenges on infrastructure for data storage which can achieve economical scaling to even more than Petabyte, massively parallel query execution, and facilities for analytical processing. Meanwhile, the rise of large data centers and cluster computers has created a new business model, cloud-based computing, where businesses and individuals can rent storage and computing capacity, rather than making the large capital investments needed to construct and provision large-scale computer installations. Cloud-based data storage and management is a rapidly expanding business. Whilst these emerging services have reduced the cost of data storage and delivery by several orders of magnitude, there is significant complexity involved in ensuring large data service can scale when needed to ensure consistent and reliable operation under peak loads. Cloud-based environment has the technical requirement to manage data center virtualization, lowers cost and boosts reliability by consolidating systems on the cloud. In addition, in an ideal world, the cloud systems should be geographically dispersed to reduce their vulnerability due to earthquakes and other catastrophes, which increase technical challenge on a great level of distributed data interoperability and mobility.

2. Scope and novelty of the workshop
This is the third workshop in CIKM conference that addresses the challenge of large data management based on cloud computing infrastructure. This workshop will bring together researchers and practitioners in cloud computing and data-intensive system design, programming, parallel algorithms, data management, scientific applications, and information-based applications to maximize performance, minimize cost and improve the scale of their endeavors.

This workshop welcomes papers that address fundamental research issues in this challenging area, with emphasis on personal and social applications of cloud-based data management. We also encourage papers to report on system level research related to cloud computing and data-intensive computing. A number of invited papers will also be solicited.

Topics of interest include, but are not limited to

Cloud computing infrastructure for big data storage and computing
Cloud privacy and security
Cloud data management of sensor stream data
Mobile cloud data management
Cloud-based system designs including architecture, scalability, economy, consistence-availability-partition (CAP), and security
Services discovery and content distribution in cloud computing infrastructures
Cross-platform interoperability
Query processing and indexing in cloud computing systems
Access control in cloud computing systems
Service-level agreements, business models, and pricing policies
Novel data-intensive computing applications
Language for massively parallel query execution
Data intensive scalable computing
Content distribution systems for big data
Data management within and across data centers
Large scale analytical methodology and algorithm

3. Submission Papers
Manuscripts should be formatted using the ACM camera-ready templates (both for MS word and Latex) available at http://www.acm.org/sigs/pubs/proceed/template.html. There are two styles on the website. Both the Strict Adherence to SIGS and the Tighter Alternate style are allowed. Papers cannot exceed 8 pages in length.

To submit a paper, go to the CloudDB2011 Submission System. Only papers submitted via the CloudDB2011 Submission System will be considered for review.

4. Important Dates

Individual Workshop Papers Due: June 29, 2011
Notification of Acceptance: July 29, 2011
Camera Ready: August 12, 2011

5. Organizing Committee
General Chairs:

Xiaofeng Meng, Renmin University of China
PC Co-Chairs:

Zhiming Ding, Institute of Software, Chinese Academy of Sciences
Haibo Hu, Hong Kong Baptist University

PC Members:

Lei Chen, The Hong Kong University of Science and Technology
Hai Jin, Huazhong University of Science and Technology
Kian-Lee Tan, National University of Singapore
Chunqiang Tang, IBM T. J. Watson Research
Mohamed Sharaf, University of Queensland
Maurizio Lenzerini, University of Rome La Sapienza
Wang-Chien Lee, Pennsylvania State University
Karu Sankaralingam, University of Wisconsin-Madison
Marcos K. Aguilera, Microsoft Research
Rajkumar Buyya, The University of Melbourne
Qiu Jie, IBM China Research Lab
Anna Liu, University of New South Wales
Sherif Sakr, National Information and Communications Technology Australia
Bin He, IBM Almaden Research Center