CloudDb: Cloud Data Management

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Past:   Proceedings on DBLP

Future:  Post a CFP for 2015 or later   |   Invite the Organizers Email

 
 

All CFPs on WikiCFP

Event When Where Deadline
CloudDB 2014 The 6th International workshop on Cloud Data Management
Apr 4, 2014 - Apr 4, 2014 Chicago, IL USA Nov 13, 2013
CloudDB 2013 The Fifth International workshop on Cloud Data Management
Oct 28, 2013 - Oct 28, 2013 San Franciso Jun 25, 2013
CloudDB 2012 The Fourth International Workshop on Cloud Data Management
Nov 2, 2012 - Nov 2, 2012 Maui, Hawaii, USA Jun 29, 2012
CloudDB 2011 Third International Workshop on Cloud Data Management
Oct 28, 2011 - Oct 28, 2011 Glasgow, Scotland, U.K. Jun 29, 2011
CloudDB 2010 Second International Workshop on Cloud Data Management
Oct 30, 2010 - Oct 30, 2010 Tornoto, Canada Jun 30, 2010
CloudDB 2009 The First International Workshop on Cloud Data Management (CloudDB2009)
Nov 6, 2009 - Nov 6, 2009 HongKong, China Jul 5, 2009
 
 

Present CFP : 2014

This workshop is dedicated to address the challenges in managing large collections of data in the cloud computing environment, and identifying information of value to business, science, government, and society. The huge volumes of data in cloud computing environments pose big infrastructure challenges, including data storage at Petabyte scale, massively parallel query execution, facilities for analytical processing, and online query processing.

Meanwhile, the emergence of large data centers and cluster computers have created a new business model, cloud-based computing, where businesses and individuals can rent storage and computing capacities, rather than make significant capital investments to construct and provision large-scale computer facilities. Cloud-based data storage and management is a rapidly expanding business. Whilst these emerging services have substantially reduced the cost of data storage and delivery, there is significant complexity involved in ensuring that they can sustain consistent and reliable operations under peak loads. A cloud-based environment has technical requirements to manage data center virtualization, lower cost and boost reliability by consolidating systems in the cloud.

In addition, cloud systems ideally should be geographically dispersed, both to reduce their vulnerability to natural disasters and other catastrophes, as well as to bring data and computation closer to a possibly global user base. This trend brings rise to new and complex technical challenges in the areas of distributed data interoperability and mobility.

Cloud computing has become a pillar of computer science industry and research, and data management in the cloud computing environment plays a key role. The CloudDB’2014 workshop aims to provide a forum for researchers and practitioners to exchange ideas and progress in the cloud data management area.

The theme of the CloudDB’2013 is to address the challenges of large data management in a cloud computing environment. This workshop welcomes papers that address fundamental research issues in this challenging area, with an 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 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
 

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