CloudDB 2009

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 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.

This is the first workshop, in conjunction with the ACM 18th Conference on Information and Knowledge Management (CIKM), 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

 * 1) Cloud computing infrastructure for big data storage and computing
 * 2) Cloud-based big data system, including architecture, scalability, economy, consistence-availability-partition (CAP), and security
 * 3) Services and data discovery and content and service distribution in cloud computing infrastructures
 * 4) Cross-platform interoperability
 * 5) Security and risk in the cloud/Security and risk in the big data management
 * 6) Service-level agreements, business models, and pricing policies
 * 7) Novel data-intensive computing applications
 * 8) Language for massively parallel query execution
 * 9) Data intensive scalable computing
 * 10) Content distribution systems for big data
 * 11) Data management within and across data centers
 * 12) Large scale analytical methodology and algorithm

Submissions
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. Please submit papers to clouddb09@gmail.com. Selected papers will be included in JCST Special Issue on Trends Changing Data Management.

Important Dates
Submission deadline: July 5th 2009

Notification date: Aug 11st 2009

Camera-ready submission deadline: Aug 20th 2009

Committees

 * Workshop Co-Chairs:
 * Prof. has workshop chair::Xiaofeng Meng, Renmin University of China, China
 * Dr. has workshop chair::Haixun Wang, IBM T. J. Watson Research, USA
 * Dr. has workshop chair::Ying Chen, IBM China Research


 * Local Arrangement Co-Chairs
 * Dr. has local chair::Jiaheng Lu, Renmin University of China, China
 * Dr. has local chair::Jie Qiu, IBM China Research Lab, China


 * Program Committee Members
 * has PC member::Lei Chen,HKUST, Hong Kong
 * has PC member::Jidong Chen, EMC China Lab, China
 * has PC member::Brian Frank Cooper, Yahoo! Research, U.S.A
 * has PC member::Hai Jin, Huazhong Univ. of Sci. and Tech., China
 * has PC member::Avinash Lakshman, Facebook, U.S.A
 * has PC member::Chen Li, University of California, Irvine, U.S.A
 * has PC member::Xiaoming Li, Peking University, China
 * has PC member::Zhanhuai Li, Northwestern Polytechnic Univ., China
 * has PC member::Xuemin Lin, Univ. of New South Wales, Australia
 * has PC member::Tok Wang Ling, National University of Singapore, Singapore
 * has PC member::Jian Pei, Simon Fraser University, Canada
 * has PC member::Adam Silberstein, Yahoo! Research, U.S.A
 * has PC member::Kian-Lee Tan, National University of Singapore, Singapore
 * has PC member::Changjie Tang, Sichuan University, China
 * has PC member::Chunqiang Tang, IBM T. J. Watson Research, U.S.A
 * has PC member::Yufei Tao, CUHK, Hong Kong
 * has PC member::Shivakumar Vaithyanathan, IBM Research, U.S.A
 * has PC member::Kyu-Young Whang, KAIST, Korea
 * has PC member::Guoren Wang, Northeastern University, China
 * has PC member::Jianliang Xu, HKBU, Hong Kong
 * has PC member::Jiangming Yang, Microsoft Research Asia, China
 * has PC member::Jun Yang, Duke University, U.S.A
 * has PC member::Sai Zeng, IBM T. J. Watson Research, U.S.A
 * has PC member::Rui Zhang, University of Melbourne Australia
 * has PC member::Aoying Zhou, Fudan University, China
 * has PC member::Lizhu Zhou, Tsinghua University, China
 * has PC member::Xiaodong Zhou, AOL China Lab, China