TY  - JOUR
AU  - Li, Jianjiang
AU  - Wu, Jie
AU  - Ma, Zhanning
PY  - 2015
TI  - Frequency and Similarity-Aware Partitioning for Cloud Storage Based on Space-Time Utility Maximization Model
JO  - Tsinghua Science and Technology
SN  - 1007-0214
SP  - 233
EP  - 245
VL  - 20
IS  - 3
AB  - With the rise of various cloud services, the problem of redundant data is more prominent in the cloud storage systems. How to assign a set of documents to a distributed file system, which can not only reduce storage space, but also ensure the access efficiency as much as possible, is an urgent problem which needs to be solved. Space-efficiency mainly uses data de-duplication technologies, while access-efficiency requires gathering the files with high similarity on a server. Based on the study of other data de-duplication technologies, especially the Similarity-Aware Partitioning (SAP) algorithm, this paper proposes the Frequency and Similarity-Aware Partitioning (FSAP) algorithm for cloud storage. The FSAP algorithm is a more reasonable data partitioning algorithm than the SAP algorithm. Meanwhile, this paper proposes the Space-Time Utility Maximization Model (STUMM), which is useful in balancing the relationship between space-efficiency and access-efficiency. Finally, this paper uses 100 web files downloaded from CNN for testing, and the results show that, relative to using the algorithms associated with the SAP algorithm (including the SAP-Space-Delta algorithm and the SAP-Space-Dedup algorithm), the FSAP algorithm based on STUMM reaches higher compression ratio and a more balanced distribution of data blocks.
UR  - https://doi.org/10.1109/TST.2015.7128935
DO  - 10.1109/TST.2015.7128935