Server Technologies in Cloud Computing and Big Data
A special issue of Future Internet (ISSN 1999-5903).
Deadline for manuscript submissions: closed (15 March 2013) | Viewed by 11017
Special Issue Editor
Interests: cloud; big data; informatics; e-science
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
“Big data is like crude oil — it needs filtering and refining to unlock its value and make it usable.” Holger Kiske (2012)
Big data usually includes data sets with sizes beyond the ability of commonly-used software tools to capture, manage, and process the data within a tolerable elapsed time. It also endure the diversity and nature of fast evolving. Big data sizes are a constantly moving target, ranging from a few dozen terabytes to many petabytes of data in a single data set. Difficulties include capture, storage, search, sharing, analysis, and visualization. The requirement of a spectrum of advanced technologies, skills, and investments, including the demands of huge amounts of external data and a lot of data services, is the reason that cloud becomes a sensible platform for big data applications. The ability of cloud computing to provide computer resources, storage, network capacity and analysis big data made the two fields are closely connected.
The special issue of Server Technologies in Big Data and Cloud Computing intends to tackle the big data issue intelligently, efficiently and effectively with the cloud technology. It will also emphasize on advances in the emerging technical and solutions on big data and cloud computing.
Yike Guo
Guest Editors
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Keywords
- Big Data applications in Cloud
- Big Data analytics in Cloud
- Cloud data management solutions
- Big Data sharing in Cloud
- DaaS, Data as a service
- Opportunistic data processing in hybrid clouds
- Dynamic provisioning for big data processing
- System Issues related to large datasets
- Big Data placement, scheduling, and optimization
- Issues of privacy, security and trust in Big Data analytics
- Fragmentation issues of Big Data
- Distributed file systems for Big Data
- Scalability issues in data storage systems
- Future research challenges in management of Big Data
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