DocumentCode :
2239040
Title :
Partition-based cloud data storage and processing model
Author :
Yawei Zhao ; Yong Wang
Author_Institution :
Coll. of Comput. & Commun., Grad. Univ. of Chinese Acad. of Sci., Beijing, China
fYear :
2012
fDate :
Oct. 30 2012-Nov. 1 2012
Firstpage :
218
Lastpage :
223
Abstract :
How to maximally use and efficiently manage cloud storage resources has become one of major problem in cloud computing area. If cloud storage capacity is limited or restrictions on a single file size, user may hire more cloud computing storage services. Data partitioning and distributed storage technologies are focused on to solve the problem that size of large dataset is limited in cloud storage. A model of partition-based data storage in cloud is put forward and its availability is discussed. Fragment partition description is given and three algorithms are designed on the basis of model. The first algorithm is about partition and storage of data, the second algorithm is about data query and connection, and the last algorithm is about fragment updated and re-partitioned. The experimental results show that the model can be applied to the situation with multiple cloud storage services and large dataset or file.
Keywords :
cloud computing; data handling; distributed processing; cloud computing storage services; cloud data processing model; cloud data storage model; cloud storage resources; distributed storage technologies; Algorithm design and analysis; Availability; Cloud computing; Distributed databases; Partitioning algorithms; Servers; Vectors; Cloud storing; Connection; Fragment; Partition; Query; Update;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cloud Computing and Intelligent Systems (CCIS), 2012 IEEE 2nd International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4673-1855-6
Type :
conf
DOI :
10.1109/CCIS.2012.6664400
Filename :
6664400
Link To Document :
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